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Data Mining with Weka (1.6: Visualizing your data)
 
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Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 6: Visualizing your data 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: 66002 WekaMOOC
The beauty of data visualization - David McCandless
 
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View full lesson: http://ed.ted.com/lessons/david-mccandless-the-beauty-of-data-visualization David McCandless turns complex data sets, like worldwide military spending, media buzz, and Facebook status updates, into beautiful, simple diagrams that tease out unseen patterns and connections. Good design, he suggests, is the best way to navigate information glut -- and it may just change the way we see the world. Talk by David McCandless.
Views: 566360 TED-Ed
Inductive Visual Miner
 
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This video is part of a series showcasing the use of the ProM process mining framework. Each video focusses on a specific process mining task or algorithm. ProM is open-source and freely available at: http://www.promtools.org In this video we introduce the Inductive visual Miner, one of the process discovery algorithms available in ProM. The Inductive visual Miner provides an interactive visualization for process exploration, performance analysis and deviation detection. A brief overview of the Inductive visual Miner is also provided in: http://ceur-ws.org/Vol-1295/paper19.pdf For more information on process mining, please visit: http://www.processmining.org/ Created by: Sander Leemans, Elham Ramezani
Views: 3298 P2Mchannel
Datawatch's New Visual Data Discovery solution
 
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Rami Chahine, product manager at Datawatch demonstrates how Datawatch provides organizations with the ability to analyze and understand Any Data Variety, regardless of structure, at Real-time Velocity, through an unmatched Visual Data Discovery environment.
Views: 2880 Datawatch
Data Visualization Lessons
 
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This video serves as a portal to 10 other curated videos on YouTube which cover the topic of "Data Visualization" and other related topics such as "Infographics". Videos: _________________________________________ 1: The value of data visualization - http://www.youtube.com/watch?v=xekEXM0Vonc Additional Reading: - Column Five (video creator) blog: http://columnfivemedia.com/news/ - Visua.ly blog post about why data visualization is so hot: http://blog.visual.ly/why-is-data-visualization-so-hot/ - Article titled "Data visualization Past,Present, and Future": http://www.perceptualedge.com/articles/Whitepapers/Data_Visualization.pdf _________________________________________ 2: What Are Infographics? - http://www.youtube.com/watch?v=x3RTS1JfMy8 Additional Reading: - Wikipedia: http://en.wikipedia.org/wiki/Infographic - An infographic explaining what infographics are: http://www.customermagnetism.com/infographics/what-is-an-infographic/ _________________________________________ 3: Big Data Week Data Visualization London - Francesco D'Orazio "10 reasons why we visualize data" - http://www.youtube.com/watch?v=npEKPZxQuns Additional Reading: - Slides used in the video: http://www.slideshare.net/Facegroup/10-reasons-why-we-visualise-data - Blog post on why we should visualize data: http://seeingcomplexity.wordpress.com/2011/03/13/why-visualize-data-we-dont-know-yet/ - Using Data Visualization to Find Insights in Data: http://datajournalismhandbook.org/1.0/en/understanding_data_7.html _________________________________________ 4: David McCandless: The beauty of data visualization - http://www.youtube.com/watch?v=pLqjQ55tz-U Additional Reading: - David McCandless website: http://www.informationisbeautiful.net/ - The Information is Beautiful Awards website: http://www.informationisbeautifulawards.com/ - Beautiful Data blog: http://beautifuldata.net/ _________________________________________ 5: I Like Pretty Graphs: Best Practices for Data Visualization Assignments - http://www.youtube.com/watch?v=pD_OvRtH0aY Additional Reading: - Eight Principles of Data Visualization blog post: http://www.information-management.com/news/Eight-Principles-of-Data-Visualization-10023032-1.html - Design principles slides: http://www.slideshare.net/gelvan/design-principles _________________________________________ 6: How to Create Infographics Part I - http://www.youtube.com/watch?v=X4-_e8zliqg Additional Reading: - Interactive tutorial on creating an infographic: http://www.asmallbrightidea.com/pages/tutorial.html - Blog post with 5 infographics to teach you how to create infographics in powerpoint: http://blog.hubspot.com/blog/tabid/6307/bid/34223/5-Infographics-to-Teach-You-How-to-Easily-Create-Infographics-in-PowerPoint-TEMPLATES.aspx _________________________________________ 7: EFFECTIVE INFORMATION VISUALIZATION by Matthias Shapiro - EP 31 - http://www.youtube.com/watch?v=_l-Dby7-JG4 Additional Reading: - Blog post on creating effective data visualizations: http://online-behavior.com/analytics/effective-data-visualization _________________________________________ 8: Data, Design, Meaning - http://www.youtube.com/watch?v=vfYul2E56fo Additional Reading: - Idan Gazit personal website: http://gazit.me/ - Collection of Idan Gazit's slides including the ones used in the videos: https://speakerdeck.com/idangazit _________________________________________ 9: Data Viz: You're Doing it Wrong - http://www.youtube.com/watch?v=i93iWza8sG8 Additional Reading: - Common Mistakes in Data visualization slides: http://www.slideshare.net/amedeevangasse/common-mistakes-in-data-visualization - Visua.ly blog post about 4 easy visualization mistakes to avoid: http://blog.visual.ly/data-visualization-mistakes-to-avoid/ _________________________________________ 10: Designing Data Visualizations with Noah Iliinsky - http://www.youtube.com/watch?v=R-oiKt7bUU8 Additional Reading: - Noah Iliinsky books published and profile: http://www.oreillynet.com/pub/au/4419 - Noah Iliinsky virtual seminar on "Telling the Right Story With Data Visualizations": http://www.uie.com/brainsparks/2012/03/16/noah-iliinsky-telling-the-right-story/ - Noah Iliinsky podcast on "The Power of Data Visualizations": http://www.uie.com/brainsparks/2012/01/27/noah-iliinsky-the-power-of-data-visualizations/ _________________________________________
Views: 1826 JohnLio07
Introduction to Data Science with R - Data Analysis Part 1
 
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Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 911665 David Langer
HWTAC Webinar 017 - Data Visualization: Strategies, Tips, and Tools
 
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HWTAC Webinar 017 - Data Visualization: Strategies, Tips, and Tools Data visualization can be a powerful tool for detecting patterns in data and for sharing data accessibly with a wide audience. This webinar will introduce the basics of data visualization with an eye towards practice, including simple tips and tricks to help create effective visualizations. The webinar will also discuss the major tools available to create static or web-based interactive visualizations. Live Q&A session included. Original broadcast: February 10, 2016 Presenter: Matt Jansen, Data Analyst, UNC Libraries Moderator: David Armstrong, PhD
Shmoocon 2012: Malware Visualization in 3D
 
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This video is part of the Infosec Video Collection at SecurityTube.net: http://www.securitytube.net Shmoocon 2012: Malware Visualization in 3D PDF :- http://www.shmoocon.org/2012/presentations/Danny_Quist-3dmalware-shmoocon2012.pdf Malware reverse engineering is greatly helped by visualization techniques. In this talk I will show you my 3D visualization enhancements to VERA for creating compelling, and useful displays of malware. This new tool provides a new method to visualize running code, show concurrent running threads of execution, visualize the temporal relationships of the code, and illustrate complicated packer original entry point detection. Real! Live! Reverse Engineering! of the past year of malware will show the utility of the program on in-the-wild samples. Danny Quist is a research scientist at Los Alamos National Laboratory and the founder of Offensive Computing, LLC. His research is in automated analysis methods for malware with software and hardware assisted techniques. He consults with both private and public sectors on system and network security. His interests include malware defense, reverse engineering, exploitation methods, virtual machines, and automatic classification systems. Danny holds a Ph.D. from the New Mexico Institute of Mining and Technology. He is the master of the Five Point Exploding Packer Technique. Danny has presented at several industry conferences including Blackhat, RSA, ShmooCon, Vizsec, and Defcon.
Views: 1713 SecurityTubeCons
Storytelling in Business: Data Storytelling
 
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This short animated video is an exclusive add-on to SAS Best Practices' "Storytelling in Business" interactive e-book by Bree Baich and Analise Polsky. In this video, Bree guides you through the art of using your data to create compelling stories! DOWNLOAD E-BOOK: STORYTELLING IN BUSINESS - THE PLOT, THE PLAYERS AND THE PATH TO DYNAMIC CUSTOMER ENGAGEMENT This book contains interactive features that work best when viewed using Adobe Acrobat and Flash. Please download the e-book to get the full experience. https://www.sas.com/content/dam/SAS/en_us/doc/whitepaper1/storytelling-in-business-109014.pdf SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 75,000 sites make better decisions faster. Since 1976, SAS has been giving customers around the world THE POWER TO KNOW®. VISIT SAS http://www.sas.com CONNECT WITH SAS SAS ► http://www.sas.com SAS Customer Support ► http://support.sas.com SAS Communities ► http://communities.sas.com Facebook ► https://www.facebook.com/SASsoftware Twitter ► https://www.twitter.com/SASsoftware LinkedIn ► http://www.linkedin.com/company/sas Google+ ► https://plus.google.com/+sassoftware Blogs ► http://blogs.sas.com RSS ►http://www.sas.com/rss
Views: 15701 SAS Software
Visual analytics _ Amir Mosavi
 
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Sweeping through skill levels and team performance of field workers in building construction projects; enhancing the multiple criteria decision making in construction industries. References: 1Hewage K.N., Gannoruwa A., Ruwanpura J.Y. (2011), Current Status of Factors Leading to Team Performance of On-Site Construction Professionals in Alberta Building Construction Projects, Canadian Journal of Civil Engineering (in press). 2Battiti, Roberto; Andrea Passerini (2010). "Brain-Computer Evolutionary Multi-Objective Optimization (BC-EMO): a genetic algorithm adapting to the decision maker." (PDF). IEEE Transactions on Evolutionary Computation 14 (15): 671--687 3Roberto Battiti and Mauro Brunato, Reactive Business Intelligence. From Data to Models to Insight, Reactive Search Srl, Italy, February 2011. In one of the Alberta's building construction projects more than 150 workers were surveyed with questionnaires and observations1. From the collected data-set direct information, via statistical methods, were achieved such as the average field experience of construction workers, the workers level of education and having certified skills, and whether workers wanted to improve their career skills or not. This survey clearly notes the urgent need for training programs to improve their present skill levels. However decision-making on how and with what rate the training program should be done is not a simple task and it has to be considered from different perspectives and criteria. Moreover from the data-set and statistical methods we can not learn how the training programs would affect team efficiencies, team spirit, and team perceptions of supervision. With the aid of data mining visualization useful and hidden information are achieved which enhance the multiple criteria decision making in construction industries. A series of visualization tools would support the final decision by clarifying the problem, its dimensions, and relation between problems parameters.
Views: 465 Amir Mosavi
People, Data and Analysis
 
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Speaker/Performer: Pat Hanrahan, Computer Graphics Laboratory, Stanford University Sponsor: CITRIS (Ctr for Info Technology Research in the Interest of Society) Abstract: Big data is a hot topic in computing. Most research has focused on automatic methods of data processing such as machine learning and natural language processing. Another important direction of research is how to build systems that can store and process massive data sets. Unfortunately, what has been lost in the discussion is how people should use data to perform analysis and make decisions. It is unlikely that people will be replaced completely by automated decision making systems in the near future. Hence, an important question to ask is what should people do and what should computers do? In this talk, I will discuss promising approaches for building interactive tools that allow people to perform data analysis more easily and effectively. Biography: Pat Hanrahan is a computer graphics researcher, the Canon USA Professor of Computer Science and Electrical Engineering in the Computer Graphics Laboratory at Stanford University. His research focuses on rendering algorithms, graphics processing units, as well as scientific illustration and visualization. As a founding employee at Pixar Animation Studios in the 1980s, Hanrahan was part of the design of the RenderMan Interface Specification and the RenderMan Shading Language. More recently, Hanrahan has served as a co-founder and Chief Scientist of Tableau Software. He has been involved with several Pixar productions, including Tin Toy, The Magic Egg, and Toy Story. In 2005, Stanford University was named the first Regional Visualization and Analytics Center (RVAC), where Hanrahan assembled a multidisciplinary team of researchers, focused on broad-ranging problems in information visualization and visual analytics.
Views: 455 CITRIS
StatQuest: t-SNE, Clearly Explained
 
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t-SNE is a popular method for making an easy to read graph from a complex dataset, but not many people know how it works. Here's the dope! Also, if you'd like to see a code example in R, here's one: http://statquest.org/2017/09/18/statquest-t-sne-clearly-explained/ This StatQuest is by ReQuest! StatQuesters wanted t-SNE to be clearly explained, and now I've gone and done it. For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/
The best stats you've ever seen | Hans Rosling
 
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http://www.ted.com With the drama and urgency of a sportscaster, statistics guru Hans Rosling uses an amazing new presentation tool, Gapminder, to present data that debunks several myths about world development. Rosling is professor of international health at Sweden's Karolinska Institute, and founder of Gapminder, a nonprofit that brings vital global data to life. (Recorded February 2006 in Monterey, CA.) TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes. TED stands for Technology, Entertainment, Design, and TEDTalks cover these topics as well as science, business, development and the arts. Closed captions and translated subtitles in a variety of languages are now available on TED.com, at http://www.ted.com/translate. Follow us on Twitter http://www.twitter.com/tednews Checkout our Facebook page for TED exclusives https://www.facebook.com/TED
Views: 2814548 TED
Analyzing And Visualizing Data With Excel 2016
 
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In this workshop, get an introduction to the latest analysis and visualization capabilities in Excel 2016. See how to import data from different sources, create mash/ups between data sources, and prepare the data for analysis. After preparing the data, learn about how business calculations - from simple to more advanced - can be expressed using DAX, how the result can be visualized and shared.
Views: 29820 Microsoft Power BI
Knowledge Graphs and Deep Learning 102
 
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In this video, we are going to look into not so exciting developments that connect Deep Learning with Knowledge Graph and GANs… let’s just hope it’s more fun than “Machine Learning Memes for Convolutional Teens”. GAN Explained Link : https://www.youtube.com/watch?v=hQv8FNaJHEA The bot in the video is R2D2, which comes after OB1's 2nd gen in Star Wars. Audio change was a bit tricky. Topics Covered in the video 1. Graph Convolutional Networks 2. Semi-supervised Learning 3. Knowledge Graphs and Ontology 4. Embedding in Knowledge Graphs 5. Adversarial Learning in Knowledge Graphs (KBGANs) Please contribute to the initiative by donating to us via Patreon because we need the money to scale up our efforts and bring creative weirdos and nerdy dreamers together. Patreon Link: https://www.patreon.com/crazymuse Even something as small as 1$ per creation can make a collective difference. Join us on slack if you want to contribute to the scripts that we write for the video. Slack Link : https://goo.gl/GFW2My Contributors for the Video 1. Script Writer : Jaley Dholakiya 2. Reviewers : Arjun Shetty, Sidharth Aiyar, Saikat Paul 3. Animator and Moderator : Jaley Dholakiya References 1. Blog on Graph Convolutional Network : https://tkipf.github.io/graph-convolutional-networks/ 2. Semi-supervised learning in Knowledge Graphs (Gaussian Field): http://mlg.eng.cam.ac.uk/zoubin/papers/zgl.pdf 3. Trans-E embedding (NIPS) : https://papers.nips.cc/paper/5071-translating-embeddings-for-modeling-multi-relational-data.pdf 4. Trans-D embedding : http://www.aclweb.org/anthology/P15-1067 5. KBGANs : https://arxiv.org/pdf/1711.04071.pdf Current Contributors on Patreon ( https://www.patreon.com/crazymuse ) 1. Aaron Mathew (main contributor) 2. Parth Parikh 3. Sean Marrett 4. Laher D 5. Abhijith N AI , Machine Learning , KBGANs, DBPedia, Facebook Graphs
Views: 2962 Crazymuse
Actuate BIRT Analytics 4.2
 
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note: VIDEO IS BEST VIEWED IN HD QUALITY / FULL SCREEN Actuate BIRT Analytics provides Advanced Analytics & Visual data mining! BIRT Analytics enables set analysis with Venn diagrams, pareto and distribution charts, profiling and correlating, and predictive analysis with time-series forecasting, association rules and decision tree analytic techniques. Contact Actuate today for a live demo! www.actuate.com
Views: 252 Mark G
Advanced Data Mining with Weka (4.6: Application: Image classification)
 
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Advanced Data Mining with Weka: online course from the University of Waikato Class 4 - Lesson 6: Application: Image classification http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/msswhT https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 7411 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: 2535843 Simply Explained - Savjee
Intro to Julia for data science
 
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Join us on July 25 (10AM PDT/1PM EDT/19:00CET/10:30PM IST) for a tutorial with Huda Nassar! Huda is a PhD candidate at Purdue and author of `MatrixNetworks.jl`. In this tutorial, she will show how to work with your data in Julia, including data processing, algorithms, and visualizations You can follow along and interact with tutorial materials without installing anything at juliabox.com. See you on the 25th! Visit http://julialang.org/ to download Julia.
Views: 12403 The Julia Language
Get Started with Oracle Data Visualization V4
 
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In Oracle Data Visualization Desktop or Oracle Analytics Cloud..... Create a new project. Sort the data, create a marquee selection, keep data elements within a marquee selection, swap data elements, add new elements, change a visualization type, and save the project. ================================= To improve the video quality, click the gear icon and set the Quality to 1080p/720p HD. For more information, see http://www.oracle.com/goto/oll and http://docs.oracle.com Copyright © 2017 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
Spherical Layout and Rendering Methods for Immersive Graph Visualization
 
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New video: https://www.youtube.com/watch?v=LQYamaU8OvA Spherical Layout and Rendering Methods for Immersive Graph Visualization Oh-Hyun Kwon, Chris Muelder, Kyungwon Lee, and Kwan-Liu Ma In Proc. IEEE Pacific Visualization Symposium, Visualization Note (Short Paper), Best Note Award, Apr 2015 PDF: http://vis.cs.ucdavis.edu/papers/ImmersiveGraphVis.pdf IEEE Xplore: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7156357
Views: 891 Oh-Hyun Kwon
Molecular Dynamics, The Shovel for Data Mining Neutron Scattering Data
 
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Some of the uses of neutron scattering experiments of disordered, biologically relevant systems as a test for molecular dynamics simulations. Also covered are how molecular dynamics simulations can be used as interpretive tools for neutron scattering data.
Views: 2686 thunderf00tCC
SAS Visual Analytics Demo for Retail
 
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http://www.sas.com/visualanalytics Learn how to use SAS Visual Analytics to identify customer segments and do Market Basket Analysis Reporting. SAS VISUAL ANALYTICS Get fast answers to even the most complex questions using data of any size – including big data in Hadoop. Guided exploration makes it easy. In-memory processing makes it fast. Advanced data visualization tools make it clear. Scalability makes it the perfect fit. And the price makes it within your reach. LEARN MORE ABOUT SAS VISUAL ANALYTICS http://www.sas.com/software/visual-analytics/overview.html TRY VISUAL ANALYTICS YOURSELF Browse sample reports or explore on your own with this cloud-based demo. http://www.sas.com/software/visual-analytics/demos/all-demos.html SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 75,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world The Power to Know.® VISIT SAS http://www.sas.com CONNECT WITH SAS SAS ► http://www.sas.com SAS Customer Support ► http://support.sas.com SAS Communities ► http://communities.sas.com Facebook ► https://www.facebook.com/SASsoftware Twitter ► https://www.twitter.com/SASsoftware LinkedIn ► http://www.linkedin.com/company/sas Google+ ► https://plus.google.com/+sassoftware Blogs ► http://blogs.sas.com RSS ►http://www.sas.com/rss
Views: 102667 SAS Software
VMD Tutorial for Beginners
 
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This VMD demonstration shows how to download a PDB file online and how to create various visual representations. This video is in support of the HHMI TIPS project (Beta Version).
Views: 61240 Vince Metzger
SocialHelix: Visualization of Sentiment Divergence in Social Media (Journal of Visualization)
 
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Social media allow people to express and promote different opinions, on which people’s sentiments to a subject often diverge when their opinions conflict.An intuitive visualization that unfolds the process of sentiment divergence from the rich and massive social media data will have far-reaching impact on various domains including social science, politics and economics. In this paper, we propose a visual analysis system, SocialHelix, to achieve this goal. SocialHelix is a novel visual design which enables users to detect and trace topics and events occurring in social media,and to understand when and why divergences occurred and how they evolved among different social groups. We demonstrate the effectiveness and usefulness of Social-Helix by conducting in-depth case studies on tweets related to the national political debates.
Views: 225 Nan Cao
Cartographic Treemaps for the Visualization of Public Healthcare Data Practice Talk by Chao Tong
 
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The following is a practice talk for the Conference on Computer Graphics and Visual Computing, 14-15 September 2017 given by Chao Tong. Chao Tong, Richard Roberts, Robert S Laramee, Daniel Thayer, Damon Berridge, Cartographic Treemaps for the Visualization of Public Healthcare Data, The Computer Graphics and Visual Computing (CGVC) Conference 2017, 14-15 September 2017, Manchester, UK PDF http://cs.swan.ac.uk/~csbob/research/cartographic/tong17cartographic.pdf Supplementary PDF: http://cs.swan.ac.uk/~csbob/research/cartographic/tong17supplementary.pdf
Views: 60 DataVisBob Laramee
Kyran Dale: Data-visualisation with Python and Javascript; Crafting a data-viz toolchain for the web
 
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While Python is fast becoming the goto language for data-processing/science, the visual fruits of that labour hit the wall of the web, where there is only one first-class language, Javascript. To develop a data-viz toolchain for the modern world, where web-presentation is increasingly mandated, making Python and Javascript play nicely is fundamental. This talk aims to show how to easily do that. Full details — http://london.pydata.org/schedule/presentation/12/
Views: 2700 PyData
Visual Analysis of Historic Hotel Visitation Patterns
 
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This video describes an interactive visual tool for exploring the visitation patterns of guests at two hotels in central Pennsylvania from 1894 to 1900. It is implemented as a coordinated multiple view visualization in Improvise, a a desktop application developed by Chris Weaver for building and browsing visual interfaces that perform highly interactive querying of multidimensional data sets. To read a full paper about this work, see: http://www.cs.ou.edu/~weaver/academic/publications/weaver-2007b.pdf For more about Improvise, visit http://www.cs.ou.edu/~weaver/improvise/index.html Please cite as: Chris Weaver, David Fyfe, Anthony Robinson, Deryck Holdsworth, Donna Peuquet, Alan M. MacEachren 2006. Visual Analysis of Historic Hotel Visitation Patterns, Video Posted on Youtube, Sept 24, 2010 (produced to accompany C. Weaver, D. Fyfe, A.C. Robinson, D. Holdsworth, D. Peuquet, A.M. MacEachren, "Visual Analysis of Historic Hotel Visitation Patterns," IEEE Symposium on Visual Analytics Science and Technology 2006, Baltimore, MD, pp. 35-42 2006.)
Views: 929 GeoVISTACenter
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
 
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While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ActiVis, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance- and subset-level. ActiVis has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ActiVis may work with different models. ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models. Minsuk Kahng, Pierre Y. Andrews, Aditya Kalro, Duen Horng (Polo) Chau. Published in IEEE Transactions on Visualization and Computer Graphics, Vol. 24, No. 1, January 2018. Presented at IEEE Conference on Visual Analytics Science and Technology (VAST), Phoenix, Arizona, USA, October 2017.
Data Analysis with Python for Excel Users
 
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A common task for scientists and engineers is to analyze data from an external source. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information. See http://apmonitor.com/che263/index.php/Main/PythonDataAnalysis
Views: 162142 APMonitor.com
Oracle DV - Custom map views on DV Desktop Analysis
 
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Adding a Custom Layer (geoJSON): http://www.oracle.com/technetwork/middleware/downloads/custom-maplayer-in-va-2887099.pdf
Views: 3009 ORACLE ANALYTICS
Berlin Marathon Data Visualization with Java
 
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Code: https://github.com/yoola/Visualization-Berlin-Marathon-Data/tree/master/InfoVis_Assignment_new/src/infovis/paracoords Documentation: https://github.com/yoola/Visualization-Berlin-Marathon-Data/blob/master/Docu_Visu.pdf Data: https://www.bmw-berlin-marathon.com/en/race-day/results-lists.html
Views: 183 yoola
Excel Data Analysis: Sort, Filter, PivotTable, Formulas (25 Examples): HCC Professional Day 2012
 
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Download workbook: http://people.highline.edu/mgirvin/ExcelIsFun.htm Learn the basics of Data Analysis at Highline Community College Professional Development Day 2012: Topics in Video: 1. What is Data Analysis? ( 00:53 min mark) 2. How Data Must Be Setup ( 02:53 min mark) Sort: 3. Sort with 1 criteria ( 04:35 min mark) 4. Sort with 2 criteria or more ( 06:27 min mark) 5. Sort by color ( 10:01 min mark) Filter: 6. Filter with 1 criteria ( 11:26 min mark) 7. Filter with 2 criteria or more ( 15:14 min mark) 8. Filter by color ( 16:28 min mark) 9. Filter Text, Numbers, Dates ( 16:50 min mark) 10. Filter by Partial Text ( 20:16 min mark) Pivot Tables: 11. What is a PivotTable? ( 21:05 min mark) 12. Easy 3 step method, Cross Tabulation ( 23:07 min mark) 13. Change the calculation ( 26:52 min mark) 14. More than one calculation ( 28:45 min mark) 15. Value Field Settings (32:36 min mark) 16. Grouping Numbers ( 33:24 min mark) 17. Filter in a Pivot Table ( 35:45 min mark) 18. Slicers ( 37:09 min mark) Charts: 19. Column Charts from Pivot Tables ( 38:37 min mark) Formulas: 20. SUMIFS ( 42:17 min mark) 21. Data Analysis Formula or PivotTables? ( 45:11 min mark) 22. COUNTIF ( 46:12 min mark) 23. Formula to Compare Two Lists: ISNA and MATCH functions ( 47:00 min mark) Getting Data Into Excel 24. Import from CSV file ( 51:21 min mark) 25. Import from Access ( 54:00 min mark) Highline Community College Professional Development Day 2012 Buy excelisfun products: https://teespring.com/stores/excelisfun-store
Views: 1517235 ExcelIsFun
Cartographic Treemaps for the Visualization of Public Healthcare Data
 
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Chao Tong, Richard Roberts, Robert S Laramee, Daniel Thayer, Damon Berridge, Cartographic Treemaps for the Visualization of Public Healthcare Data, The Computer Graphics and Visual Computing (CGVC) Conference 2017, forthcoming, 14-15 September 2017, Manchester, UK PDF http://cs.swan.ac.uk/~csbob/research/cartographic/tong17cartographic.pdf Abstract: The National healthcare Service (NHS) in the UK collects a massive amount of high-dimensional, region-centric data concerning individual healthcare units throughout Great Britain. It is challenging to visually couple the large number of multivariate attributes about each region unit together with the geo-spatial location of the clinical practices for visual exploration, analysis, and comparison. We present a novel multivariate visualization we call a cartographic treemap that attempts to combine the space-filling advantages of treemaps for the display of hierarchical, multivariate data together with the relative geo-spatial location of NHS practices in the form of a modified cartogram. It offers both space filling and geospatial error metrics that provide the user with interactive control over the space-filling versus geographic error trade-off. The result is a visualization that offers users a more space efficient overview of the complex, multivariate healthcare data coupled with the relative geo-spatial location of each practice to enable and facilitate exploration, analysis, and comparison. We evaluate the two metrics and demonstrate the use of our approach on real, large high-dimensional NHS data and derive a number of multivariate observations based on healthcare in the UK as a result. We report the reaction of our software from two domain experts in health science.
Views: 91 DataVisBob Laramee
BI Connector | Tableau Analytics for OBIEE Using BI Connector
 
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Learn how to: 1. Create stunning Tableau visualizations directly from OBIEE data in minutes 2. Reuse OBIEE metadata and security model for Tableau visualization 3. Share your analysis with executives using Tableau Server 4. Build new data insights in Tableau from existing OBIEE reports Download the free trial at https://www.biconnector.com/freetrial/ and visualize Oracle BI (OBIEE) Subject Area and Reports with your Tableau, Power BI or Qlik in minutes. For more information Visit: Website - http://www.biconnector.com LinkedIn - https://www.linkedin.com/showcase/bi-connector/ Facebook - https://www.facebook.com/biconnector Twitter - https://twitter.com/bi_connector?lang=en Don't forget to subscribe!
Views: 216 BI Connector
SAS Visual Analytics 7.3 (on SAS 9) Decision Tree Demo
 
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http://www.sas.com/visualanalytics The powerful decision tree algorithms in SAS Visual Analytics help you go beyond reporting and put analytics into the hands of more users. GET FREE TRIAL OF SAS VISUAL ANALYTICS Browse sample reports or explore on your own with this cloud-based demo. SAS VISUAL ANALYTICS Data visualization software that offers full-size power for any size budget. Get fast answers to even the most complex questions using data of any size – including big data in Hadoop. Guided exploration makes it easy. In-memory processing makes it fast. Advanced data visualization tools make it clear. Scalability makes it the perfect fit. And the price makes it within your reach. LEARN MORE ABOUT SAS VISUAL ANALYTICS http://www.sas.com/tryva DOWNLOAD SAS VISUAL ANALYTICS FACT SHEET http://www.sas.com/content/dam/SAS/en_us/doc/factsheet/sas-visual-analytics-105682.pdf SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 75,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world The Power to Know.® VISIT SAS http://www.sas.com CONNECT WITH SAS SAS ► http://www.sas.com SAS Customer Support ► http://support.sas.com SAS Communities ► http://communities.sas.com Facebook ► https://www.facebook.com/SASsoftware Twitter ► https://www.twitter.com/SASsoftware LinkedIn ► http://www.linkedin.com/company/sas Google+ ► https://plus.google.com/+sassoftware Blogs ► http://blogs.sas.com RSS ►http://www.sas.com/rss
Views: 6700 SAS Software
Data Mining Tool: extra features
 
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Some extra features of the Data Mining Tool. Heatmaps and Gene Set Enrichment.
Views: 59 QMRIBioinf
Datawatch and Angoss - fast data prep and analytics
 
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In today’s high speed analytics marketplace it is no surprise that data volumes and sources are expanding at an accelerating rate. On a daily basis, analysts spend up to 80 percent of their time collecting data from numerous sources such as the web, pdf’s, text reports, log files and many more to prepare it for analysis. Analysts are further challenged to make this data actionable with the use of predictive modeling. The alliance between Datawatch and Angoss offers businesses the fastest and most easy-to-use applications which significantly reduce time spent on data extraction, data preparation, and predictive modeling. Datawatch Monarch works with a wide range of report formats including PDF, XML, HTML, text, spool and ASCII files. Analysts can easily access data from invoices, sales reports, balance sheets, customer lists, inventory, logs and more. Data is then cleansed and consolidated into a single file for immediate consumption into any of the Angoss software applications. Analysts can now focus on translating their data into business value, without having to code, using the most easy-to-use and analyst recognized data mining and modeling techniques, such as Angoss’ best in class Decision Trees and Strategy Trees, to uncover important patterns within a dataset, identify good predictors, and produce accurate, stable and actionable predictions. Let us help you provide your business with the fastest and easiest tools for data acquisition, preparation, and business analytics.
Views: 349 Datawatch
Advanced Data Mining with Weka (5.4: Invoking Weka from Python)
 
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Advanced Data Mining with Weka: online course from the University of Waikato Class 5 - Lesson 4: Invoking Weka from Python http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/7XXl63 https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 2934 WekaMOOC
03 Visualizing Data in RapidMiner Studio
 
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Download the sample tutorial files at http://static.rapidminer.com/education/getting_started/Follow-along-Files.zip
Views: 10471 RapidMiner, Inc.
Modeling Data Streams Using Sparse Distributed Representations
 
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In this screencast, Jeff Hawkins narrates the presentation he gave at a workshop called "From Data to Knowledge: Machine-Learning with Real-time and Streaming Applications." The workshop was held May 7-11, 2012 at the University of California, Berkeley. Slides: http://www.numenta.com/htm-overview/05-08-2012-Berkeley.pdf Abstract: Sparse distributed representations appear to be the means by which brains encode information. They have several advantageous properties including the ability to encode semantic meaning. We have created a distributed memory system for learning sequences of sparse distribute representations. In addition we have created a means of encoding structured and unstructured data into sparse distributed representations. The resulting memory system learns in an on-line fashion making it suitable for high velocity data streams. We are currently applying it to commercially valuable data streams for prediction, classification, and anomaly detection In this talk I will describe this distributed memory system and illustrate how it can be used to build models and make predictions from data streams. Live video recording of this presentation: http://www.youtube.com/watch?v=nfUT3UbYhjM General information can be found at https://www.numenta.com, and technical details can be found in the CLA white paper at https://www.numenta.com/faq.html#cla_paper.
Views: 20203 Numenta
SmartAdP: Visual Analytics of Large-scale Taxi Trajectories for Selecting Billboard Locations
 
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The author's personal website: http://dongyu.name More information please refer to the paper: http://dongyu.name/papers/tvcg_2016_dongyu_smartadp.pdf Online System: http://smartadp.chinacloudapp.cn/ Abstract: The problem of formulating solutions immediately and comparing them rapidly for billboard placements has plagued advertising planners for a long time, owing to the lack of efficient tools for in-depth analyses to make informed decisions. In this study, we attempt to employ visual analytics that combines the state-of-the-art mining and visualization techniques to tackle this problem using large-scale GPS trajectory data. In particular, we present SmartAdP, an interactive visual analytics system that deals with the two major challenges including finding good solutions in a huge solution space and comparing the solutions in a visual and intuitive manner. An interactive framework that integrates a novel visualization-driven data mining model enables advertising planners to effectively and efficiently formulate good candidate solutions. In addition, we propose a set of coupled visualizations: a solution view with metaphor-based glyphs to visualize the correlation between different solutions; a location view to display billboard locations in a compact manner; and a ranking view to present multi-typed rankings of the solutions. This system has been demonstrated using case studies with a real-world dataset and domain-expert interviews. Our approach can be adapted for other location selection problems such as selecting locations of retail stores or restaurants using trajectory data.
Views: 40 Dongyu Liu
Flight Delay Analysis using Python and Amazon Web Services.
 
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Analyzing the American Airlines Data-Set for Flight Delay Prediction using Python and Amazon Web Services.
Views: 342 Anant Gupta
DEFCON 18: Social Networking Special Ops: Extending Data Visualization Tools for Faster Pwnage 4/4
 
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Speaker: Chris "The Suggmeister" Sumner If you're ever in a position when you need to pwn criminals via social networks or see where Tony Hawk likes to hide skateboards around the world, this talk is for you. The talk is delivered in two parts, both of which are intended to shine a fun light on visual social network analysis. The first part introduces how you can extend the powerful data visualization tool, Maltego to speed up and automate the data mining and analysis of social networks. I'll show how I analyzed skateboard legend, Tony Hawk's twitter hunt and highlight how you could use the same techniques to set up your very own backyard miniature ECHELON. The second part illustrates how these techniques have been used to enumerate a 419 scam, infiltrate the scammers social network and expose deeper, more sinister links to organized crime. I focus specifically on Twitter and Facebook, demonstrating how you can graphically map and analyze social relationships using the Twitter API's, publicly available Facebook profiles, screen scraping and some clunky regex." Related to this talk is the DEF CON Twitter Hunt Each day at DEF CON you will have an opportunity to blag yourself a sweet limited edition DEF CON-ized skateboard deck. There may also be a couple of signed Tony Hawk decks slung in for good measure too... who knows. You will have to follow @TheSuggmeister during DEF CON to know where to look. He'll be tweeting clues which lead to prizes. Hashtag #DCTH' For presentations, whitepapers or audio version of the Defcon 18 presentations visit: http://defcon.org/html/links/dc-archives/dc-18-archive.html
Views: 709 Christiaan008
Moneyball (2011) Movie Trailer - HD - Brad Pitt
 
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The story of Oakland A's general manager Billy Beane's successful attempt to put together a baseball club on a budget by employing computer-generated analysis to draft his players. Director: Bennett Miller Writers: Steven Zaillian (screenplay), Aaron Sorkin (screenplay) Stars: Brad Pitt, Robin Wright and Jonah Hill Via: http://movies.yahoo.com/trailers/
Views: 2389191 Movieclips Trailers
5 Simple Steps to Create Meaningful Features from Clickstream Data - Shir Meir Lador
 
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This talk was presented on Pycon Israel 2017. http://il.pycon.org/2017/ https://twitter.com/pyconil https://www.facebook.com/pyconisrael/
Views: 340 PyCon Israel
Defocon 16 - DAVIX Visualization Workshop
 
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This video is part of the Infosec Video Collection at SecurityTube.net: http://www.securitytube.net Defocon 16 - DAVIX Visualization Workshop https://www.defcon.org/images/defcon-16/dc16-presentations/davix/defcon-16-manual_davix_0.5.0_v1.0.pdf Need help understanding your gigabytes of application logs or network captures? Your OS performance metrics do not make sense? Then DAVIX, the live CD for visualizing IT data, is your answer! To simplify the analysis of vast amounts of security data, visualization is slowly penetrating the security community. There are many free tools available for analysis and visualization of data. To simplify the use of these tools, the open source project DAVIX was put to life and is released this year at BlackHat/DEFCON. At this Bring Your Own Laptop workshop we will introduce you to DAVIX. The workshop starts with an introduction to the set of available tools, the integrated manual, as well as customizing the CD to your needs. In a second part, you can use DAVIX to analyze a set of provided packet captures. In the end we will show some of the visualizations created by the participants. Be prepared for pretty and meaningful pictures! For you to be able to participate in the analysis part of the workshop, you should bring an Intel or AMD x86 based notebook with at least 1GB of memory and a wireless LAN adapter. To avoid problems with the Wireless card setup we strongly recommend that you run DAVIX in VMware Player or VMware Fusion in NAT mode. The DAVIX ISO image should be downloaded before the workshop from the davix.secviz.org homepage. The network capture files will be made available during the workshop.
Views: 244 SecurityTubeCons
Heuristics Miner Basic
 
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This is the first video in a series showcasing the use of the ProM process mining framework. Each video focusses on a specific process mining task or algorithm. ProM is open-source and freely available at: http://www.promtools.org In this video we introduce the Heuristics Miner, one of the process discovery algorithms available in ProM. The Heuristics Miner is easy to use, quick and can handle noisy event logs. The theory behind the Heuristics Miner is described in detail in: http://dx.doi.org/10.1109/CIDM.2011.5949453 and http://is.ieis.tue.nl/staff/aweijters/WP166.pdf For more information on process mining, please visit: http://www.processmining.org/ Created by: Elham Ramezani, Maikel van Eck, Eduardo González López de Murillas Special Thanks: Sander Leemans, Rafal Kocielnik, Alfredo Bolt, Sebastiaan van Zelst, Shegnan Guo
Views: 6573 P2Mchannel
What is a Neural Network? | How Deep Neural Networks Work | Neural Network Tutorial | Simplilearn
 
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This Neural Network tutorial will help you understand what is deep learning, what is a neural network, how deep neural network works, advantages of neural network, applications of neural network and the future of neural network. Deep Learning uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Most deep learning methods involve artificial neural networks, modeling how our brains work. Deep Learning forms the basis for most of the incredible advances in Machine Learning. Neural networks are built on Machine Learning algorithms to create an advanced computation model that works much like the human brain. Now, let us deep dive into this video to understand how a neural network actually works along with some real-life examples. Below topics are explained in this neural network Tutorial: 1. What is Deep Learning? 2. What is an artificial network? 3. How does neural network work? 4. Advantages of neural network 5. Applications of neural network 6. Future of neural network To learn more about Deep Learning, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the slides here: https://goo.gl/Hk7cJ1 Watch more videos on Deep Learning: https://www.youtube.com/playlist?list=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip #DeepLearning #Datasciencecourse #DataScience #SimplilearnMachineLearning #DeepLearningCourse Simplilearn’s Deep Learning course will transform you into an expert in deep learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our deep learning course, you'll master deep learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as deep learning scientist. Why Deep Learning? It is one of the most popular software platforms used for deep learning and contains powerful tools to help you build and implement artificial neural networks. Advancements in deep learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in deep learning models, learn to operate TensorFlow to manage neural networks and interpret the results. And according to payscale.com, the median salary for engineers with deep learning skills tops $120,000 per year. You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to: 1. Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline 2. Implement deep learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before 3. Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces 4. Build deep learning models in TensorFlow and interpret the results 5. Understand the language and fundamental concepts of artificial neural networks 6. Troubleshoot and improve deep learning models 7. Build your own deep learning project 8. Differentiate between machine learning, deep learning and artificial intelligence There is booming demand for skilled deep learning engineers across a wide range of industries, making this deep learning course with TensorFlow training well-suited for professionals at the intermediate to advanced level of experience. We recommend this deep learning online course particularly for the following professionals: 1. Software engineers 2. Data scientists 3. Data analysts 4. Statisticians with an interest in deep learning Learn more at: https://www.simplilearn.com/deep-learning-course-with-tensorflow-training?utm_campaign=What-is-a-nEURAL-nETWORK-VB1ZLvgHlYs&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn’s courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simp... - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 9014 Simplilearn
MicroStrategy - Data Mining & Predictive Analytics - Online Training Video by MicroRooster
 
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Source: MicroRooster.blogspot.com Format: A MicroStrategy Online Training Video blog. Description: An introduction to Data Mining & Predictive Analytics using MicroStrategy. This demo explains how to use MicroStrategy for performing advanced data science analysis. Must have some understanding of basic data mining to take advantage of this entry level demo.
Views: 16574 MicroRooster

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