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Introduction to Data Mining: Basic Vocabulary
 
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All great learning opportunities are built on a solid foundation. This data mining fundamentals series is jam-packed with all the background information, technical terminology, and basic knowledge that you will need to hit the ground running. In part 1 of this data mining video series, we cover what data is and the basic vocabulary associated with it. Topics: – Data and Data Types – Data Quality – Data Preprocessing – Similarity and Dissimilarity – Data Exploration and Visualization -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 3600+ employees from over 742 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8LhN0 See what our past attendees are saying here: https://hubs.ly/H0f8LhR0 -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... -- Vimeo: https://vimeo.com/datasciencedojo
Views: 28896 Data Science Dojo
Data Mining, Classification, Clustering, Association Rules, Regression, Deviation
 
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Complete set of Video Lessons and Notes available only at http://www.studyyaar.com/index.php/module/20-data-warehousing-and-mining Data Mining, Classification, Clustering, Association Rules, Sequential Pattern Discovery, Regression, Deviation http://www.studyyaar.com/index.php/module-video/watch/53-data-mining
Views: 85823 StudyYaar.com
R Tutorial For Beginners | R Programming Tutorial l R Language For Beginners | R Training | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R Tutorial (R Tutorial Blog: https://goo.gl/mia382) will help you in understanding the fundamentals of R tool and help you build a strong foundation in R. Below are the topics covered in this tutorial: 1. Why do we need Analytics ? 2. What is Business Analytics ? 3. Why R ? 4. Variables in R 5. Data Operator 6. Data Types 7. Flow Control 8. Plotting a graph in R Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #Rtutorial #Ronlinetraining #Rforbeginners #Rprogramming How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 419034 edureka!
Machine Learning & Artificial Intelligence: Crash Course Computer Science #34
 
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So we've talked a lot in this series about how computers fetch and display data, but how do they make decisions on this data? From spam filters and self-driving cars, to cutting edge medical diagnosis and real-time language translation, there has been an increasing need for our computers to learn from data and apply that knowledge to make predictions and decisions. This is the heart of machine learning which sits inside the more ambitious goal of artificial intelligence. We may be a long way from self-aware computers that think just like us, but with advancements in deep learning and artificial neural networks our computers are becoming more powerful than ever. Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios Want to know more about Carrie Anne? https://about.me/carrieannephilbin The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list=PL1mtdjDVOoOqJzeaJAV15Tq0tZ1vKj7ZV Want to find Crash Course elsewhere on the internet? Facebook - https://www.facebook.com/YouTubeCrash... Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids
Views: 393629 CrashCourse
Data Structures and Algorithms Complete Tutorial Computer Education for All
 
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Computer Education for all provides complete lectures series on Data Structure and Applications which covers Introduction to Data Structure and its Types including all Steps involves in Data Structures:- Data Structure and algorithm Linear Data Structures and Non-Linear Data Structure on Stack Data Structure on Arrays Data Structure on Queue Data Structure on Linked List Data Structure on Tree Data Structure on Graphs Abstract Data Types Introduction to Algorithms Classifications of Algorithms Algorithm Analysis Algorithm Growth Function Array Operations Two dimensional Arrays Three Dimensional Arrays Multidimensional arrays Matrix operations Operations on linked lists Applications of linked lists Doubly linked lists Introductions to stacks Operations on stack Array based implementation of stack Queue Data Structures Operations on Queues Linked list based implementation of queues Application of Trees Binary Trees Types of Binary Trees Implementation of Binary Trees Binary Tree Traversal Preorder Post order In order Binary Search Tree Introduction to Sorting Analysis of Sorting Algorithms Bubble Sort Selection Sort Insertion Sort Shell Sort Heap Sort Merge Sort Quick Sort Applications of Graphs Matrix representation of Graphs Implementations of Graphs Breadth First Search Topological Sorting Subscribe for More https://www.youtube.com/channel/UCiV37YIYars6msmIQXopIeQ Find us on Facebook: https://web.facebook.com/Computer-Education-for-All-1484033978567298 Java Programming Complete Tutorial for Beginners to Advance | Complete Java Training for all https://youtu.be/gg2PG3TwLx4
How to Clean Up Raw Data in Excel
 
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Al Chen (https://twitter.com/bigal123) is an Excel aficionado. Watch as he shows you how to clean up raw data for processing in Excel. This is also a great resource for data visualization projects. Subscribe to Skillshare’s Youtube Channel: http://skl.sh/yt-subscribe Check out all of Skillshare’s classes: http://skl.sh/youtube Like Skillshare on Facebook: https://www.facebook.com/skillshare Follow Skillshare on Twitter: https://twitter.com/skillshare Follow Skillshare on Instagram: http://instagram.com/Skillshare
Views: 77056 Skillshare
ROC Curves and Area Under the Curve (AUC) Explained
 
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An ROC curve is the most commonly used way to visualize the performance of a binary classifier, and AUC is (arguably) the best way to summarize its performance in a single number. As such, gaining a deep understanding of ROC curves and AUC is beneficial for data scientists, machine learning practitioners, and medical researchers (among others). SUBSCRIBE to learn data science with Python: https://www.youtube.com/dataschool?sub_confirmation=1 JOIN the "Data School Insiders" community and receive exclusive rewards: https://www.patreon.com/dataschool RESOURCES: - Transcript and screenshots: https://www.dataschool.io/roc-curves-and-auc-explained/ - Visualization: http://www.navan.name/roc/ - Research paper: http://people.inf.elte.hu/kiss/13dwhdm/roc.pdf LET'S CONNECT! - Newsletter: https://www.dataschool.io/subscribe/ - Twitter: https://twitter.com/justmarkham - Facebook: https://www.facebook.com/DataScienceSchool/ - LinkedIn: https://www.linkedin.com/in/justmarkham/
Views: 279072 Data School
Neuromation - the knowledge mining era
 
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Cryptonomos will hold a token sale for Neuromation that is creating a distributed platform of synthetic data ecosystem. The enormous computing capacity that will become available on the platform will be game-changing for wide AI adoption by the Enterprise. Neuromation is creating a platform to allow users to create dataset generators, generate massive datasets, train deep learning models. Users will also be able to trade datasets and models in the platform marketplace. Neuromation engages crypto-currency miners in computationally intensive tasks of data generation and model training. By performing these tasks they will be mining Neuromation Tokens. Tokens for the Neuromation platform are already available for purchase on pre-sale via Cryptonomos. Buy tokens: https://neuromation.cryptonomos.com Telegram RU: https://t.me/icocryptonomosrus Telegram EN: https://t.me/Cryptonomos_ICOs
Views: 3186 Cryptonomos Platform
Smart Health Prediction using data mining by Customsoft
 
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Data mining is a new powerful technology which is of high interest in computer world. It is a sub field of computer science that uses already existing data in different databases to transform it into new researches and results.
Views: 228 Custom-Soft
Data Mining with Weka (1.1: Introduction)
 
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Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 1: Introduction http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 121904 WekaMOOC
Data Mining with Weka (1.3: Exploring datasets)
 
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Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 3: Exploring datasets http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 77836 WekaMOOC
How does a blockchain work - Simply Explained
 
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What is a blockchain and how do they work? I'll explain why blockchains are so special in simple and plain English! 💰 Want to buy Bitcoin or Ethereum? Buy for $100 and get $10 free (through my affiliate link): https://www.coinbase.com/join/59284524822a3d0b19e11134 📚 Sources can be found on my website: https://www.savjee.be/videos/simply-explained/how-does-a-blockchain-work/ 🐦 Follow me on Twitter: https://twitter.com/savjee ✏️ Check out my blog: https://www.savjee.be ✉️ Subscribe to newsletter: https://goo.gl/nueDfz 👍🏻 Like my Facebook page: https://www.facebook.com/savjee
Views: 2535839 Simply Explained - Savjee
1 Introduction and Background- Data Warehouse and Data Mining
 
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http://www.atozsky.com/ https://www.facebook.com/atozsky.computer/ All credits goes to NIELIT, Delhi INDIA
Views: 422 AtoZ COMPUTER
Natural Language Processing (NLP) & Text Mining Tutorial Using NLTK | NLP Training | Edureka
 
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** NLP Using Python: - https://www.edureka.co/python-natural-language-processing-course ** This Edureka video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and much more along with a demo on each one of the topics. The following topics covered in this video : 1. The Evolution of Human Language 2. What is Text Mining? 3. What is Natural Language Processing? 4. Applications of NLP 5. NLP Components and Demo Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV --------------------------------------------------------------------------------------------------------- Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Instagram: https://www.instagram.com/edureka_learning/ --------------------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 16077 edureka!
R Programming For Beginners | R Language Tutorial | R Tutorial For Beginners | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R Programming Tutorial For Beginners (R Tutorial Blog: https://goo.gl/mia382) will help you in understanding the fundamentals of R and will help you build a strong foundation in R. Below are the topics covered in this tutorial: 1. Variables 2. Data types 3. Operators 4. Conditional Statements 5. Loops 6. Strings 7. Functions Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #Rtutorial #Ronlinetraining #Rforbeginners #Rprogramming How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 299173 edureka!
How Bitcoin Works in 5 Minutes (Technical)
 
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A short introduction to how Bitcoin Works. Want more? Check out my new in-depth course on the latest in Bitcoin, Blockchain, and a survey of the most exciting projects coming out (Ethereum, etc): https://app.pluralsight.com/library/courses/bitcoin-decentralized-technology Lots of demos on how to buy, send, store (hardware, paper wallet). how to use javascript to send bitcoin. How to create Ethereum Smart Contract, much more. Written Version: http://www.imponderablethings.com/2014/04/how-bitcoin-works-in-5-minutes.html Less technical version: https://www.youtube.com/watch?v=t5JGQXCTe3c Donation address: 1K7A6wsyxj6fThtMYcNu6X8bLbnNKovgtP Germain caption translation provided by adi331 : 19s6rqRfHa19w7wcgwtCumPs1vdLDj1VVo (thanks!!)
Views: 5643327 CuriousInventor
Mod-01 Lec-04 Clustering vs. Classification
 
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Pattern Recognition by Prof. C.A. Murthy & Prof. Sukhendu Das,Department of Computer Science and Engineering,IIT Madras.For more details on NPTEL visit http://nptel.ac.in
Views: 20343 nptelhrd
JS-Reduce: Defending Your Data from Sequential Background Knowledge Attacks - IEEE 2012 Projects
 
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JS-Reduce: Defending Your Data from Sequential Background Knowledge Attacks - IEEE 2012 Projects More Details: Visit http://clickmyproject.com/index.php?main_page=product_info&cPath=1_37&products_id=97 Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-778-1155 Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us : [email protected]
Views: 442 Clickmyproject
Data Mining with Weka (5.3: Data mining and ethics)
 
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Data Mining with Weka: online course from the University of Waikato Class 5 - Lesson 3: Data mining and ethics http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/5DW24X https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 10850 WekaMOOC
Statistical Aspects of Data Mining (Stats 202) Day 1
 
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Google Tech Talks June 26, 2007 ABSTRACT This is the Google campus version of Stats 202 which is being taught at Stanford this summer. I will follow the material from the Stanford class very closely. That material can be found at www.stats202.com. The main topics are exploring and visualizing data, association analysis, classification, and clustering. The textbook is Introduction to Data Mining by Tan, Steinbach and Kumar. Googlers are welcome to attend any classes which they think might be of interest to them. Credits: Speaker:David Mease
Views: 214884 GoogleTechTalks
Data Warehousing & Data Mining
 
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Heyy guys here is some information on Data Warehousing and Data Mining! ========================= Background Song: Disfigure - Blank [NCS Release] Song Artist: No Copyright Sounds
Views: 522 Brandon The Crab
BADM 1.1: Data Mining Applications
 
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This video was created by Professor Galit Shmueli and has been used as part of blended and online courses on Business Analytics using Data Mining. It is part of a series of 37 videos, all of which are available on YouTube. For more information: www.dataminingbook.com twitter.com/gshmueli facebook.com/dataminingbook Here is the complete list of the videos: • Welcome to Business Analytics Using Data Mining (BADM) • BADM 1.1: Data Mining Applications • BADM 1.2: Data Mining in a Nutshell • BADM 1.3: The Holdout Set • BADM 2.1: Data Visualization • BADM 2.2: Data Preparation • BADM 3.1: PCA Part 1 • BADM 3.2: PCA Part 2 • BADM 3.3: Dimension Reduction Approaches • BADM 4.1: Linear Regression for Descriptive Modeling Part 1 • BADM 4.2 Linear Regression for Descriptive Modeling Part 2 • BADM 4.3 Linear Regression for Prediction Part 1 • BADM 4.4 Linear Regression for Prediction Part 2 • BADM 5.1 Clustering Examples • BADM 5.2 Hierarchical Clustering Part 1 • BADM 5.3 Hierarchical Clustering Part 2 • BADM 5.4 K-Means Clustering • BADM 6.1 Classification Goals • BADM 6.2 Classification Performance Part 1: The Naive Rule • BADM 6.3 Classification Performance Part 2 • BADM 6.4 Classification Performance Part 3 • BADM 7.1 K-Nearest Neighbors • BADM 7.2 Naive Bayes • BADM 8.1 Classification and Regression Trees Part 1 • BADM 8.2 Classification and Regression Trees Part 2 • BADM 8.3 Classification and Regression Trees Part 3 • BADM 9.1 Logistic Regression for Profiling • BADM 9.2 Logistic Regression for Classification • BADM 10 Multi-Class Classification • BADM 11 Ensembles • BADM 12.1 Association Rules Part 1 • BADM 12.2 Association Rules Part 2 • Neural Networks: Part I • Neural Nets: Part II • Discriminant Analysis (Part 1) • Discriminant Analysis: Statistical Distance (Part 2) • Discriminant Analysis: Misclassification costs and over-sampling (Part 3)
Views: 2696 Galit Shmueli
Bioinformatics part 1 What is Bioinformatics
 
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For more information, log on to- http://shomusbiology.weebly.com/ Download the study materials here- http://shomusbiology.weebly.com/bio-materials.html Bioinformatics Listeni/ˌbaɪ.oʊˌɪnfərˈmætɪks/ is an interdisciplinary field that develops and improves on methods for storing, retrieving, organizing and analyzing biological data. A major activity in bioinformatics is to develop software tools to generate useful biological knowledge. Bioinformatics uses many areas of computer science, mathematics and engineering to process biological data. Complex machines are used to read in biological data at a much faster rate than before. Databases and information systems are used to store and organize biological data. Analyzing biological data may involve algorithms in artificial intelligence, soft computing, data mining, image processing, and simulation. The algorithms in turn depend on theoretical foundations such as discrete mathematics, control theory, system theory, information theory, and statistics. Commonly used software tools and technologies in the field include Java, C#, XML, Perl, C, C++, Python, R, SQL, CUDA, MATLAB, and spreadsheet applications.[1][2][3] Source of the article published in description is Wikipedia. I am sharing their material. Copyright by original content developers of Wikipedia. Link- http://en.wikipedia.org/wiki/Main_Page
Views: 213235 Shomu's Biology
Turn Data into Knowledge
 
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What if you could harness technology and information more effectively to catapult your business? This video explores how businesses are using the latest tools to advance from data aggregation to digital transformation. The goal? Turning data into knowledge. Enjoy this video from CCC. And if you’d like to learn more about ways to harness enterprise data science to accelerate product time-to-market, and make smarter business decisions, visit www.copyright.com/data to access a new white paper Enterprise Data Science: Transition from the Era of Big Data to the Knowledge Era. Winner of a Silver Telly Award in the category Branded Content: Directing. http://www.tellyawards.com/winners/2018/branded-content/craft-directing Winner of a Bronze Telly Award in the category Branded Content: Use of graphics. http://www.tellyawards.com/winners/2018/branded-content/craft-use-of-graphic
Database and Big Data
 
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This course introduces important database concepts, including data modeling, database design, and data extraction. Students will also learn data analysis skills they need to transform raw data into useful business information and knowledge for decision-making and problem solving. Students explore relational design, data warehousing, data mining, data visualization, data search, knowledge management, business intelligence, data querying, basic analytics, and reporting.
Views: 770 [email protected]
Decision Tree (CART) - Machine Learning Fun and Easy
 
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Decision Tree (CART) - Machine Learning Fun and Easy ►FREE YOLO GIFT - http://augmentedstartups.info/yolofreegiftsp ►KERAS Course - https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML Decision tree is a type of supervised learning algorithm (having a pre-defined target variable) that is mostly used in classification problems. A tree has many analogies in real life, and turns out that it has influenced a wide area of machine learning, covering both classification and regression (CART). So a decision tree is a flow-chart-like structure, where each internal node denotes a test on an attribute, each branch represents the outcome of a test, and each leaf (or terminal) node holds a class label. The topmost node in a tree is the root node. ------------------------------------------------------------ Support us on Patreon ►AugmentedStartups.info/Patreon Chat to us on Discord ►AugmentedStartups.info/discord Interact with us on Facebook ►AugmentedStartups.info/Facebook Check my latest work on Instagram ►AugmentedStartups.info/instagram Learn Advanced Tutorials on Udemy ►AugmentedStartups.info/udemy ------------------------------------------------------------ To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out http://augmentedstartups.info/home Please Like and Subscribe for more videos :)
Views: 115569 Augmented Startups
INTRODUCTION TO DATA MINING IN HINDI
 
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Buy Software engineering books(affiliate): Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2whY4Ke Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2wfEONg Software Engineering: A Practitioner's Approach (India) by McGraw-Hill Higher Education https://amzn.to/2PHiLqY Software Engineering by Pearson Education https://amzn.to/2wi2v7T Software Engineering: Principles and Practices by Oxford https://amzn.to/2PHiUL2 ------------------------------- find relevant notes at-https://viden.io/
Views: 106639 LearnEveryone
RStudio Tutorial For Beginners | RStudio Installation  | R Tutorial | R Training | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka RStudio Tutorial For Beginners will help you in understanding the need for Rstudio and how it is used. Check out our blog: R Tutorial – A Beginner’s Guide to Learning R Programming( https://goo.gl/UeKg5g ) Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #RStudio #Rtutorial #Ronlinetraining #Rforbeginners #Rprogramming How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 37695 edureka!
Statistical Process Control (SPC) in Hindi – (Part 1). SPC  हिंदी में सीखे।
 
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Understand what is Statistical Process Control (SPC) in Hindi. This is part 1 of the video, watch concluding part 2 , to cover rest of the content. SPC क्या है हिंदी में सीखे। ये पहला भाग है , प्रोग्राम को पूरा समझने के लिए इसका दूसरा भाग भी अवस्य देखे। Watch other videos from ‘Quality HUB India’- https://www.youtube.com/channel/UCdDEcmELwWVr_77GpqldKmg/videos • Subscribe to my channel ‘Quality HUB India’ for getting notification. • Like, comment & Share the video with your colleague and friends Link to buy My books 1. Mistake-Proofing Simplified: An Indian Perspective: https://www.amazon.in/gp/product/8174890165/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=8174890165&linkCode=as2&tag=qhi-21 2. Management Thoughts on Quality for Every Manager: https://www.amazon.in/gp/product/B0075MCLTO/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B0075MCLTO&linkCode=as2&tag=qhi-21 Gadgets I use and Link to buy 1. OnePlus 5 - Mobile https://www.amazon.in/gp/product/B01MXZW51M/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B01MXZW51M&linkCode=as2&tag=qhi-21 2. HP 14-AM122TU 14-inch Laptop https://www.amazon.in/gp/product/B06ZYLLT8G/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B06ZYLLT8G&linkCode=as2&tag=qhi-21 3. Canon EOS 700D 18MP Digital SLR Camera https://www.amazon.in/gp/product/B00VT61IKA/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B00VT61IKA&linkCode=as2&tag=qhi-21 4. Sonia 9 Feet Light Stand LS-250 https://www.amazon.in/gp/product/B01K7SW2OQ/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B01K7SW2OQ&linkCode=as2&tag=qhi-21 5. Sony MDR-XB450 On-Ear EXTRA BASS Headphones https://www.amazon.in/gp/product/B00NFJGUPW/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B00NFJGUPW&linkCode=as2&tag=qhi-21 6. QHM 602 USB MINI SPEAKER https://www.amazon.in/gp/product/B00L393EXC/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B00L393EXC&linkCode=as2&tag=qhi-21 7. Photron Tripod Stedy 400 with 4.5 Feet Pan Head https://www.amazon.in/gp/product/B00UBUMCNW/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B00UBUMCNW&linkCode=as2&tag=qhi-21 8. Tie Clip Collar mic Lapel https://www.amazon.in/gp/product/B00ITOD6NM/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B00ITOD6NM&linkCode=as2&tag=qhi-21 9. Hanumex Generic Green BackDrop Background 8x12 Ft for Studio Backdrop https://www.amazon.in/gp/product/B06W53TMDR/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B06W53TMDR&linkCode=as2&tag=qhi-21 10. J 228 Mini Tripod Mount + Action Camera Holder Clip Desktop Self-Tripod For Camera https://www.amazon.in/gp/product/B072JXX9DB/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B072JXX9DB&linkCode=as2&tag=qhi-21 11. Seagate Backup Plus Slim 1TB Portable External Hard Drive https://www.amazon.in/gp/product/B00GASLJK6/ref=as_li_tl?ie=UTF8&camp=3638&creative=24630&creativeASIN=B00GASLJK6&linkCode=as2&tag=qhi-21 Watch other Videos from ‘Quality HUB India’ 1. Process Capability Study (Cp,Cpk, Pp & Ppk) - https://www.youtube.com/watch?v=5hBRE0uji5w 2. What is Six Sigma ?Learn Six Sigma in 30 minutes- https://www.youtube.com/watch?v=1oiKYydbrSw 3. Failure Mode and Effects Analysis (FMEA) - https://www.youtube.com/watch?v=UxSBUHgb1V0&t=25s 4. Statistical Process Control (SPC) in Hindi – https://www.youtube.com/watch?v=WiVjjoeIrmc&t=115s 5. Measurement System Analysis (MSA) (Part 1) - https://www.youtube.com/watch?v=GGwaZeMmZS8&t=25s 6. Advanced Product Quality Planning(APQP) - https://www.youtube.com/watch?v=FaawYoPsUYE&t=35s 7. ‘Quality Circles' - https://www.youtube.com/watch?v=kRp9OIANgG8&t=25s 8. What is 'Cost of Quality' and 'Cost of Poor Quality' - https://www.youtube.com/watch?v=IsCRylbHni0&t=25s 9. How to perfectly define a problem ? 5W and 1H approach - https://www.youtube.com/watch?v=JXecodDxBfs&t=55s 10. What is 'Lean Six Sigma' ? Learn the methodology with benefits. - https://www.youtube.com/watch?v=86XJqf1IhQM&t=41s 11. What is KAIZEN ? 7 deadly Waste (MUDA) and benefit of KAIZEN - https://www.youtube.com/watch?v=TEcE-cKk1qI&t=115s 12. What is '5S' Methodology? (Hindi)- https://www.youtube.com/watch?v=dW8faNOX91M&t=25s 13. 7 Quality Control Tools - (Part 1) Hindi - https://www.youtube.com/watch?v=bQ9t3zoM0NQ&t=88s 14. "KAIZEN" in HINDI- https://www.youtube.com/watch?v=xJpbHTc3wmo&t=25s 15. 'PDCA' or 'Deming Cycle'. Plan-DO-Check-Act cycle - https://www.youtube.com/watch?v=Kf-ax6qIPVc 16. Overall Equipment Effectiveness (OEE) - https://www.youtube.com/watch?v=5OM5-3WVtd0&feature=youtu.be 17. Why-Why Analysis? - Root Cause Analysis Tool - https://www.youtube.com/watch?v=Uxn6N6OJvwA
Views: 188876 Quality HUB India
MDM-L01T04: Medical Data Mining \ Introduction & Scientific Background - [Health Care]
 
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Don't forget to subscribe to get more videos!!
Views: 34 Health Care
Introduction to text mining with Voyant
 
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In this introduction to text mining with Voyant I cover: 1) Data cleaning (text editors, Notepad++ and Sublime Text) 2) Loading your text into Voyant 3) Expectations, what Voyant can and cannot do 4) Working with common visualization tools and making possible connections 5) Exporting visualizations
Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With Python | Edureka
 
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( **Natural Language Processing Using Python: - https://www.edureka.co/python-natural-language-processing-course ** ) This video will provide you with a detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this video: 0:46 - Introduction to Big Data 1:45 - What is Text Mining? 2:09- What is NLP? 3:48 - Introduction to Stemming 8:37 - Introduction to Lemmatization 10:03 - Applications of Stemming & Lemmatization 11:04 - Difference between stemming & Lemmatization Subscribe to our channel to get video updates. Hit the subscribe button above https://goo.gl/6ohpTV ----------------------------------------------------------------------------------------------- Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ----------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).
Views: 2063 edureka!
How to start a Business Analytics Career in India ? - Skills required, Pay scale, Job opportunities
 
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Get the latest interview tips,Job notifications,top MNC openings,placement papers and many more only at Freshersworld.com(www.freshersworld.com?src=Youtube). The major role of a BA is – data mining, statistical analysis, predictive modelling and multivariate test. Business Analytics career in India has emerged as the preferred role of choice in IT and ITES industries. The Business Analyst is also required to support decision making roles with real-time analysis. Business Analysts also work closely with the senior management and provide support in data-driven decision making that impacts matters related to product development to marketing. There is a continued strong demand for business analysts especially in India where candidates can land opportunities in IT and ITES industries. According to one article, India has at least 1.2 million business analysts and by 2020 India is pegged to have the highest number of business analysts. Some of the major sectors where Business Analysts have a promising start are retail, banking, healthcare, ecommerce, hospitality, manufacturing etc. Kick-start a Business Analytics career in India One of the most promising career paths in IT today, the job description for business analysts sometimes converge analytics and project management roles. If you are interested in a Business Analyst role, a background in mathematics and engineering is a must, backed by good analytical and communication skills. However, there are those who believe candidates with a business background can also make a career in BA. By upskilling themselves with short online courses, these candidates can also get a good grip on business analytics and start a career. Skills required by Business Analytics candidate: A Business Analyst should be proficient in applied statistics, have knowledge of statistical suite such as SAS, R, SPSS, should know SQL, Hive, knowledge of testibg framework and a working knowledge of BI tools such as Qlik, Tableau, Spot fire among others. Skills may vary depending on the organization’s requirement. However, this is a basic knowledge framework required for making the cut. How can candidates with a business background start a Business Analytics career? While most engineers gravitate towards the data engineering and information management field, candidates with a business background can easily transition into the Business Analyst role. MBA holders can sharpen their skills by a) enrolling in analytics courses, b) participating in mentoring sessions and boot camps to lands their dream job. And though companies don’t expect deep knowledge of tools, a basic understanding can help in landing the right job. Job opportunities for Business Analysts: From leading financial institutions, to consultancies such as Deloitte, E&Y, and global retailers Target, Walmart and online leader Amazon require Business Analytics professionals. Top Employers: Some of the top Business Analytics companies to work for are: • Tata Consultancy Services • Cognizant • Accenture • GENPACT • Wipro • Infosys • IBM • Deloitte • HPE Some of the startups that provide an excellent opportunity to pursue Business Analytics career are Fractal Analytics, Mu Sigma Analytics and Absolut Data. Pay scale: One of the most sought after jobs, business analysts have a rare blend of business and analytical skills and are rewarded with good pay packages. The average salary of senior business analyst is INR 8,59,025 per year. The average salary of BA is INR 6,44,857 per year. Download our app today to manage recruitment whenever and where ever you want : Link :https://play.google.com/store/apps/details?id=com.freshersworld.jobs&hl=en ***Disclaimer: This is just a training video for candidates and recruiters. The name, logo and properties mentioned in the video are proprietary property of the respective organizations. The Preparation tips and tricks are an indicative generalized information. In no way Freshersworld.com, indulges into direct or indirect promotion of the respective Groups or organizations.
Ontologies
 
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Dr. Michel Dumontier from Stanford University presents a lecture on "Ontologies." Lecture Description Ontology has its roots as a field of philosophical study that is focused on the nature of existence. However, today's ontology (aka knowledge graph) can incorporate computable descriptions that can bring insight in a wide set of compelling applications including more precise knowledge capture, semantic data integration, sophisticated query answering, and powerful association mining - thereby delivering key value for health care and the life sciences. In this webinar, I will introduce the idea of computable ontologies and describe how they can be used with automated reasoners to perform classification, to reveal inconsistencies, and to precisely answer questions. Participants will learn about the tools of the trade to design, find, and reuse ontologies. Finally, I will discuss applications of ontologies in the fields of diagnosis and drug discovery. View slides from this lecture: https://drive.google.com/open?id=0B4IAKVDZz_JUVjZuRVpMVDMwR0E About the Speaker Dr. Michel Dumontier is an Associate Professor of Medicine (Biomedical Informatics) at Stanford University. His research focuses on the development of methods to integrate, mine, and make sense of large, complex, and heterogeneous biological and biomedical data. His current research interests include (1) using genetic, proteomic, and phenotypic data to find new uses for existing drugs, (2) elucidating the mechanism of single and multi-drug side effects, and (3) finding and optimizing combination drug therapies. Dr. Dumontier is the Stanford University Advisory Committee Representative for the World Wide Web Consortium, the co-Chair for the W3C Semantic Web for Health Care and the Life Sciences Interest Group, scientific advisor for the EBI-EMBL Chemistry Services Division, and the Scientific Director for Bio2RDF, an open source project to create Linked Data for the Life Sciences. He is also the founder and Editor-in-Chief for a Data Science, a new IOS Press journal featuring open access, open review, and semantic publishing. Please join our weekly meetings from your computer, tablet or smartphone. Visit our website to learn how to join! http://www.bigdatau.org/data-science-seminars
Learning Classifier Systems in a Nutshell
 
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This video offers an accessible introduction to the basics of how Learning Classifier Systems (LCS), also known as Rule-Based Machine Learning (RBML), operate to learn patterns and make predictions. To simplify these concepts, we have focused on a generic ‘Michigan-style LCS’ algorithm architecture designed for supervised learning. The example algorithm described in this video is probably closest to the UCS algorithm described by Bernadó-Mansilla and Garrell-Guiu in their 2003 publication. However, the modern concept of the LCS algorithm is the result of founding work by John Henry Holland (https://en.wikipedia.org/wiki/John_Henry_Holland) While this video focuses on how the algorithm itself works, here we provide a brief background on why LCS algorithms are valuable and unique compared to other machine learning strategies. LCSs are a family of advanced machine learning algorithms that learn to represent patterns of association in a distributed, piece-wise fashion. These systems break down associations between independent and dependent variables into simple ‘IF:THEN’ statements. This makes them very flexible and adaptive learners that can approach data in a model free and assumption free manner. Research and development of LCS algorithms was initially focused on reinforcement learning problems such as behavior modeling, but in the last decade, the advantages of applying these systems as supervised learners has become clear. In particular LCS algorithms have been demonstrated to perform particularly well on the detection, modeling and characterization of complex, multi-variate, epistatic, or heterogeneous patterns of association. Additionally, LCS algorithms are naturally multi-objective (accuracy, and generality), niche learners, and can easily be thought of as implicit ensemble learners. Furthermore, LCSs can be adapted to handle missing data values, imbalanced data, discrete and continuous features, as well as binary class, multi-class, and regression learning/prediction. The flagship benchmark problem for these systems has traditionally been the n-bit multiplexer problem. The multiplexer is a binary classification problem that is both epistatic and heterogeneous where no single feature is predictive of class on its own. This benchmark can be scaled up in dimensional complexity to include the 6-bit, 11-bit, 20-bit, 37-bit, 70-bit, and 135-bit variations. Most other machine learners struggle, in particular, with heterogeneous relationships. As of 2016, our own LCS algorithm, called ‘ExSTraCS’ was still the only algorithm in the world to report having the ability to solve the 135-bit multiplexer problem directly. For a complete introduction, review, and roadmap to LCS algorithms, check out my review paper from 2009: http://dl.acm.org/citation.cfm?id=1644491 The first introductory textbook on LCS algorithms (authored by Will Browne and myself) will be published by 'Springer' this fall: (link will be found here once it's available) To follow research and software developed by Ryan Urbanowicz PhD on rule-based machine learning methods or other topics, check out the following links. http://www.ryanurbanowicz.com https://github.com/ryanurbs To follow research and software development by Jason H. Moore PhD, and his Computation Genetics Lab at the University of Pennsylvania’s Institute for Biomedical Informatics, check out the following links. http://epistasis.org/ http://upibi.org/
Views: 6403 ryan urbanowicz
ggplot2 Tutorial | ggplot2 In R Tutorial | Data Visualization In R | R Training | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This "ggplot2 Tutorial" by Edureka is a comprehensive session on the ggplot2 in R. This tutorial will not only get you started with the ggplot2 package, but also make you an expert in visualizing data with the help of this package. This tutorial will comprise of these topics: 1) Base R Graphics 2) Grammar of Graphics 3) GGPLOT2 package Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #Rtutorial #Ronlinetraining #ggplot2 #ggplotinr How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 30145 edureka!
Data Mining with Weka (1.5: Using a filter )
 
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Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 5: Using a filter http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 65385 WekaMOOC
But what *is* a Neural Network? | Deep learning, chapter 1
 
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Subscribe to stay notified about new videos: http://3b1b.co/subscribe Support more videos like this on Patreon: https://www.patreon.com/3blue1brown Or don't. It's your call really, no pressure. Special thanks to these supporters: http://3b1b.co/nn1-thanks Additional funding provided by Amplify Partners. For any early-stage ML entrepreneurs, Amplify would love to hear from you: [email protected] Full playlist: http://3b1b.co/neural-networks Typo correction: At 14:45, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that! For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nielsen's way if you get something out of it. And second, it's centered around walking through some code and data which you can download yourself, and which covers the same example that I introduce in this video. Yay for active learning! https://github.com/mnielsen/neural-networks-and-deep-learning I also highly recommend Chris Olah's blog: http://colah.github.io/ For more videos, Welch Labs also has some great series on machine learning: https://youtu.be/i8D90DkCLhI https://youtu.be/bxe2T-V8XRs For those of you looking to go *even* deeper, check out the text "Deep Learning" by Goodfellow, Bengio, and Courville. Also, the publication Distill is just utterly beautiful: https://distill.pub/ Lion photo by Kevin Pluck If you want to contribute translated subtitles or to help review those that have already been made by others and need approval, you can click the gear icon in the video and go to subtitles/cc, then "add subtitles/cc". I really appreciate those who do this, as it helps make the lessons accessible to more people. Music by Vincent Rubinetti: https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown ------------------ 3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that). If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended Various social media stuffs: Website: https://www.3blue1brown.com Twitter: https://twitter.com/3Blue1Brown Patreon: https://patreon.com/3blue1brown Facebook: https://www.facebook.com/3blue1brown Reddit: https://www.reddit.com/r/3Blue1Brown
Views: 3510550 3Blue1Brown
Job Roles For DATA ENTRY OPERATOR – Entry Level,DataBase,Arts,Science,WPM, Data Management
 
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Job Roles For DATA ENTRY OPERATOR : Know more about job roles and responsibility in DATA ENTRY . Coming to DATA ENTRY OPERATOR opportunities for freshers in India,Visit http://www.freshersworld.com?src=Youtube for detailed information,Job Opportunities,Education details and Career growth of DATA ENTRY OPERATOR. No matter what your educational background is, data entry operator jobs are available for all fresh candidates. People usually do not seek this position thinking that this is a low-level job. As a matter of fact, it is not lower than any other entry level position in corporate world. The main job of a data entry operator is to update, add and maintain data in a system or managing databases. The data entry operator is expected to insert or add data related to the company (both text and numerical) from a source file provided by the company. The candidate should also verify and sort the information as per given instruction. Other operational work includes generating routine reports and filing documents related to their work. Mostly, freshers with bachelor degree in arts and science are sought for this position. Even diploma candidates are opted for this position by many companies. Usually, candidates with professional degree, master degree or doctorate would not be sought for this position. The basic requirements are a) Knowledge and savvy in computer operation b) Expertise in MS-Office and other related software c) High typing speed – minimum market requirement is 40 WPM with 95% accuracy. d) Basic communication skills in English Usually, the candidates with good computer skill would be sought without regards to their educational background. Rotational shifts are rare and both male and female are sought. This job is also available in working-from-home option in some companies. There are short terms courses with certification for data entry offered by many institutions. Though it is not an essential certification, it would give a competitive edge over other candidates. Those who have working knowledge of Tally are sought for accountancy related data entry with a slightly higher pay. The same goes for those with commerce related educational background. With an increase in growth of BPO industry in India, there is a very high demand for data entry specialists. With one to three years experience in data entry, one can apply for jobs related to data management, document imaging, data mining, data processing and other related fields. If you want to grow in the same field, with three or more years of experience in data entry job, you can apply for senior data entry position or data analyzer positions. With more experience, you can apply for managerial positions like transaction processor, document processor and many others. Your scope is not restricted to back office operations. Candidates with a few years of experience in data entry can take up operational related jobs in KPO and customer service department. Yet, they would be considered as fresher in the new department. This job is for those who do not have a fancy degree and yet, want to take up corporate job. With this job, entry into corporate world becomes easy for all kinds of candidates. The academic excellence is not an important qualification for this job. Thus, candidates with backlog and those with moderate communication skill can apply for this position if, their typing skill is excellent. For more jobs & career information and daily job alerts, subscribe to our channel and support us. You can also install our Mobile app for govt jobs for getting regular notifications on your mobile. Freshersworld.com is the No.1 job portal for freshers jobs in India. Check Out website for more Jobs & Careers. http://www.freshersworld.com?src=Youtube - - ***Disclaimer: This is just a career guidance video for fresher candidates. The name, logo and properties mentioned in the video are proprietary property of the respective companies. The career and job information mentioned are an indicative generalised information. In no way Freshersworld.com, indulges into direct or indirect recruitment process of the respective companies.
What is E-Commerce in Hindi  (Basic Information for Beginners)
 
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Types of E-Commerce : https://youtu.be/m7x6zYEBYEM What is EDI in eCommerce ?: https://youtu.be/zN237-EpFQI ------------------------------------------------------------------------- What is E-Commerce in Hindi what is ecommerce meaning in hindi ecommerce explained e commerce means in hindi ecommerce means introduction to ecommerce in hindi ecommerce theory -------------------------------------------------------------- This is my Blog: http://mystudymafia.blogspot.in/2018/02/e-commerce-stands-for-electronic.html
Views: 150744 STUDY Mafia
Basic Concepts of Object Oriented Programming (HINDI)
 
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Views: 1486840 easytuts4you
Person Entities: Lessons learned by a data provider
 
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Talk by John W. Chapman (OCLC, Inc.). Title: Person Entities: Lessons learned by a data provider Abstract: Continuing the longstanding research program by OCLC in the field of linked data, recent projects have focused on creating sets of entities of high interest for any organization wanting to utilize linked data paradigms. Through intensive mining and clustering of WorldCat bibliographic data, name and subject authority files, and other related data sets, OCLC has produced over 300 million entity representations. These clusters pull together and represent creative works, and persons related to those works. OCLC has engaged with a number of libraries and organizations to create and experiment with this data. A pilot project during October 2015-February 2016 to explore new methods of providing access to Person entities provided a number of new directions and insights. The core purpose of the work is to understand how these entities might best be leveraged to make library workflows more efficient, and to improve the quality of metadata produced in the library sector. This presentation will provide a background on data used in the project, as well as the development of services and APIs to provision the data. It will address challenges and opportunities in the area of creating and managing entities, and ways in which they could be improved and enriched over time. SWIB16 Conference, 28 - 30 November 2016, Bonn, Germany http://swib.org/swib16/ #swib16 Licence: CC-BY-SA https://creativecommons.org/licenses/by-sa/3.0/
Views: 65 SWIB
Accounting Concepts and Principles: Accounting Basics and Fundamentals
 
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This lesson will teach you 7 Accounting Concepts and Principles that underly all accounting studies and practice. To add relevance, reliability and comparability throughout the behaviour of all accountants globally, accountants follow these 7 accounting concepts in all their activities. This lesson should be the first topic you study in your Introduction to Accounting knowledge journey as it lays the fundamentals for all future accounting study. You will learn about: * The Entity Concept 2:07 * The Accounting Period Concept 5:08 * The Cost Principle 8:02 * The Matching Concept 11:34 * The Profit Recognition Principle 13:49 * The Conservatism Principle 16:50 * The Going Concern Principle 20:15 Each concept is explained both with the theory and an example or two. If you apply all these concepts & principles throughout your activity as a student, bookkeeper or accountant then you will be a successful accounting professional. So whether you are a accounting student, bookkeeper or MBA candidate with a finance subject, you should find value in this lesson. You can also get in touch anytime if you need any further help or clarification beyond the lesson. Just check out the contact details in our YouTube Channel. --------------------- Thumbnail Portrait: Photo by Bruce Mars from Pexels --------------------- This video was brought to you by AccoFina. Subscribe to the Channel: https://goo.gl/84Sfeg Or just check out the Channel Page: https://goo.gl/yTj9Bs Here’s AccoFina’s Most Popular YouTube Video: https://goo.gl/Jbv685 And here’s AccoFina’s Latest YouTube Upload: https://goo.gl/wDM83Y AccoFina Website, Product Pages and Social Networking: 1) Website (includes Free Spreadsheets, Free Books and Free Calculators) http://www.accofina.com 2) Amazon Author Page: http://www.amazon.com/author/axeltracy 3) Udemy Instructor Page https://www.udemy.com/u/axeltracy/ 4) Facebook http://www.facebook.com/accofinaDotCom 5) Twitter http://www.twitter.com/accofina 6) Google+ http://plus.google.com/+accofina
Views: 162389 AccoFina
Big Data Unit 10: Lesson 3:  Physics and Random Variables II
 
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We describe the DIKW pipeline for the analysis of this type of physics experiment and go through details of analysis pipeline for the LHC ATLAS experiment. We give examples of event displays showing the final state particles seen in a few events. We illustrate how physicists decide whats going on with a plot of expected Higgs production experimental cross sections (probabilities) for signal and background.
An Interview: Professor meets a Scientist at Cyberc 2017
 
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Visit www.Cyberc.org and submit your research paper to attend this great event. CyberC (International Conference on Cyber-enabled distributed computing and knowledge discovery) is an international conference on cyber-enabled technology. It covers cyber-networks, data mining, cyber security, distributed computing, mobile computing, cognitive computing, cloud computing, computing tools, applications, and system performance. CyberC offers a forum for presentation and discussion of innovative ideas, research results, applications, and experience for network-enabled distributed computing and knowledge discovery technologies. This video is an interview and the background information is below. Dr. Chih-Lin I , Chief Scientist, Wireless Technologies, China Mobile Research Institute Chih-Lin I received her Ph.D. degree in electrical engineering from Stanford University. She has been working at multiple world-class companies and research institutes leading the R&D, including AT&T Bell Labs; Director of AT&T HQ, Director of ITRI Taiwan, and VPGD of ASTRI Hong Kong. She received the IEEE Trans. COM Stephen Rice Best Paper Award, is a winner of the CCCP National 1000 Talent Program, and has won the 2015 Industrial Innovation Award of IEEE Communication Society for Leadership and Innovation in Next-Generation Cellular Wireless Networks. In 2011, she joined China Mobile as its Chief Scientist of wireless technologies, established the Green Communications Research Center, and launched the 5G Key Technologies R&D. She is spearheading major initiatives including 5G, C-RAN, high energy efficiency system architectures, technologies and devices; and green energy. Keynote Topic in CyberC 2017: SDN/NFV via SBA&CUDU Abstract: From Green to Soft, the revolutionary path towards future 5G has been charted out. Since its proposal in 2012, SDN/NFV has been viewed as an essential element towards this end. In this talk, we will share CMCC’s endeavor on the path towards SOFT 5G. In particular, it will be presented how the philosophy of SDN/NFV has been adopted and implemented in our networks, from SBA-based cthe ore network to CU-DU-based radio access networks. In fact, C-RAN, which has been proposed by CMCC in 2009, has conceived the NFV idea since its birth. The achievements at the earlier stage will be introduced, including the deployment of centralization, trials on CoMP, some pioneering work on RAN virtualization. Then, the latest progress on RAN cloudification/virtualization will be detailed from various perspectives such as hypervisor, HW platform and MANO systems. Finally other key 5G components such as big data analytics, mobile edge computing etc. will also be touched. Anup Kumar, PhD, Professor, University of Louisville, Kentucky, USA Anup Kumar completed his Ph.D. from North Carolina State University and is currently a Professor of CECS Department at the University of Louisville. He is also the Director of Mobile Information Network and Distributed Systems (MINDS) Lab. His research interests include web services, wireless networks, distributed system modeling, and simulation. He has co-edited a book titled, “Handbook of Mobile Systems: Applications ands Services” published by CRC press in 2012. He is a Senior Member of IEEE. Topic: Access Control Security – Why and How Access Control Policies are Tested and Verified? Abstract: SDN/NFV, cloud, and many other online systems relies Access control (AC) to protect the secret financial, enterprise, organization, healthcare, defense, and various IT resources/services. In order to protect the classified resources, the security specialist needs to compose a set of AC policies (e.g., in XACML policies) to prevent unintended access. However, the current AC policies are composed and deployed into an AC system without comprehensive security tests and verifications. This results in many AC flaws (e.g., information or service leaks) in the systems and these AC flaws are normally hidden from us until observable damages (e.g., secret data leakage) are caused. This paves the way for cybersecurity hackers or insiders to steal the IT assets by exploring the access control weakness. Recently NIST has released several specifications in order to help government and enterprises to enhance the nation's critical access control security, such as NIST SP 800-192: Verification and Test Methods for Access Control Policies/Models. As stated by NIST, many of the access control incidents (e.g., data breaches, insiders) are caused by misconfigured access control policies. In this talk, we will explore the state-of-art access control policy testing and verification approaches. Examples are (i) Access Control Polity Tool and (ii) Security Policy Tool, which respectively delivers a solution for testing, analyzing, inspecting, and correcting the access control flaws. Primary information can be found at http://csrc.nist.gov/groups/SNS/acpt/acpt-beta.html and https://securitypolicytool.com .
Bitcoin: How Cryptocurrencies Work
 
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Whether or not it's worth investing in, the math behind Bitcoin is an elegant solution to some complex problems. Hosted by: Michael Aranda Special Thanks: Dalton Hubble Learn more about Cryptography: https://www.youtube.com/watch?v=-yFZGF8FHSg ---------- Support SciShow by becoming a patron on Patreon: https://www.patreon.com/scishow ---------- Dooblydoo thanks go to the following Patreon supporters—we couldn't make SciShow without them! Shout out to Bella Nash, Kevin Bealer, Mark Terrio-Cameron, Patrick Merrithew, Charles Southerland, Fatima Iqbal, Benny, Kyle Anderson, Tim Curwick, Will and Sonja Marple, Philippe von Bergen, Bryce Daifuku, Chris Peters, Patrick D. Ashmore, Charles George, Bader AlGhamdi ---------- Like SciShow? Want to help support us, and also get things to put on your walls, cover your torso and hold your liquids? Check out our awesome products over at DFTBA Records: http://dftba.com/scishow ---------- Looking for SciShow elsewhere on the internet? Facebook: http://www.facebook.com/scishow Twitter: http://www.twitter.com/scishow Tumblr: http://scishow.tumblr.com Instagram: http://instagram.com/thescishow ---------- Sources: https://bitinfocharts.com/ https://chrispacia.wordpress.com/2013/09/02/bitcoin-mining-explained-like-youre-five-part-2-mechanics/ https://www.youtube.com/watch?v=Lx9zgZCMqXE https://www.youtube.com/watch?v=nQZUi24TrdI https://bitcoin.org/en/how-it-works http://www.forbes.com/sites/investopedia/2013/08/01/how-bitcoin-works/#36bd8b2d25ee http://www.makeuseof.com/tag/how-does-bitcoin-work/ https://blockchain.info/charts/total-bitcoins https://en.bitcoin.it/wiki/Controlled_supply https://www.bitcoinmining.com/ http://bitamplify.com/mobile/?a=news Image Sources: https://commons.wikimedia.org/wiki/File:Cryptocurrency_Mining_Farm.jpg
Views: 2634738 SciShow
We Know More than We Can Tell | Jodi Asbell-Clarke | TEDxBeaconStreet
 
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To unleash the potential of all learners, we need to start looking at what people can do, not just what they can say. "Many of The cognitive differences of neurodiverse students (learners with Autism, ADD, Dyslexia and other cognitive functions that make school difficult) may also empower them with creativity, resilience, and innovative approaches to problem-solving. -Our education system struggles to measure and support these different ways of thinking, denying diverse learners their optimal learning opportunities and robbing Our future workforce of The talent and ingenuity that diverse learners offer. -digital environments—including games, augmented, virtual and mixed reality—offer new ways to measure learners’ implicit knowledge, not relying on a test. games have The “stickiness” that motivate diverse learners to drill deeper, pursue new challenges, and persist to solve problems. -digital environments generate data logs and educational data mining models---algorithms that identify common patterns of behavior to see where each learner struggles and succeeds in a digital experience--- can inform teachers and designers How to customize learning experience for each and every learner." Dr. Jodi Asbell-Clarke is the co-founder and co-director of the Educational Gaming Environments Group (EdGE) at TERC. TERC is a non-profit research and development organization focusing on innovative, technology-based STEM education. Jodi and the EdGE team of game designers, educators, and researchers study implicit STEM learning in digital games to transform science education. A believer in Seymore Papert’s term ‘hard fun’, EdGE applies it to education by designing challenging free-choice STEM learning games that are within the grasp of the player motivating them to keep playing and learn advanced science content in their free time. EdGE researchers also use educational data mining to measure implicit learning in games, and work with educators to understand how it can be leveraged to measure classroom learning of related STEM content. EdGE is currently researching how AR and VR can enhance learning, especially for learners with particular skills and challenges, such as ADHD and autism. Before joining TERC, Jodi dreamed of being an astronaut and went to Houston where she was an onboard software verification analyst for IBM during the first 25 space shuttle missions. She also taught Physics and Astrophysics to some of the brightest students in the country at the laboratory school at University of Illinois. Jodi’s academic background includes an MA in Math, an MSc in Astrophysics, and a PhD in Education. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx
Views: 1469 TEDx Talks
Lecture 01 - The Learning Problem
 
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The Learning Problem - Introduction; supervised, unsupervised, and reinforcement learning. Components of the learning problem. Lecture 1 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website - http://work.caltech.edu/telecourse.html Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommons.org/licenses/by-nc-nd/3.0/ This lecture was recorded on April 3, 2012, in Hameetman Auditorium at Caltech, Pasadena, CA, USA.
Views: 849877 caltech
Master of Science in Data Analytics at Clarkson University
 
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Clarkson University offers a master of science degree in the highly sought-after field of data analytics. Data analytics or "big data" is one of the most in-demand career paths in today’s marketplace, leading to high-skill/high paying jobs in pharma, the entertainment industries, marketing intelligence, high-tech, engineering firms, Fortune 500s, fast-growing startups and many other businesses. Organizations across industries collect large amounts of data for a variety of reasons: to gain a competitive advantage, to improve the efficiency of operations, to reduce fraud/waste/abuse, or to better understand customers, among others. "Everyone from corporations and governments to startups and small businesses are looking for the insights in today's mountains of big data," says Business Professor Boris Jukic, director of business analytics. "But they are realizing they need specially trained and highly skilled people who can turn these endless streams of data into useful insight and actionable intelligence." The new data analytics degree will provide students with the skills to be effective professionals in the field of identifying, acquiring, managing, presenting, analyzing and interpreting large amounts of data in a variety of professional fields and organizational settings. Jukic says that no matter what a student's academic or professional background is, they can get the analytical skills and learn the critical methodology to make the most of big data. "These skills will enable them to get positions with job titles like data analyst, data analytics manager, and data scientist, among others," he says. The program is interdisciplinary, meaning that students will take classes from faculty in all of Clarkson's schools. "This cross-disciplinary approach of science, business and engineering with all of our schools contributing to the degree will expand the network of opportunities available to students who complete the program," adds Jukic. Graduates of the program will develop skill sets in the core areas of data mining and knowledge discovery; managing big data: modeling, retrieving, transforming and organization of big data; and data visualization, presentation and interpretation. Students with a variety of professional and academic backgrounds can apply to the new program. The 33-credit program is structured to fit into one academic year, including a sponsored, paid internship during the summer. Foundation courses in calculus, mathematical statistics and basic programming can be completed as part of an undergraduate degree program or, for students with a non-technical background, prerequisite courses are available during the summer. For more information or to apply for the master of science degree in data analytics program, go to http://www.clarkson.edu/bigdata, e-mail [email protected] or call 866-333-6613.
Views: 1844 Clarkson University

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