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Twitter Sentiment Analysis - Learn Python for Data Science #2
 
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In this video we'll be building our own Twitter Sentiment Analyzer in just 14 lines of Python. It will be able to search twitter for a list of tweets about any topic we want, then analyze each tweet to see how positive or negative it's emotion is. The coding challenge for this video is here: https://github.com/llSourcell/twitter_sentiment_challenge Naresh's winning code from last episode: https://github.com/Naresh1318/GenderClassifier/blob/master/Run_Code.py Victor's Runner up code from last episode: https://github.com/Victor-Mazzei/ml-gender-python/blob/master/gender.py I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ More on TextBlob: https://textblob.readthedocs.io/en/dev/ Great info on Sentiment Analysis: https://www.quora.com/How-does-sentiment-analysis-work Great sentiment analysis api: http://www.alchemyapi.com/products/alchemylanguage/sentiment-analysis Read over these course notes if you wanna become an NLP god: http://cs224d.stanford.edu/syllabus.html Best book to become a Python god: https://learnpythonthehardway.org/ Please share this video, like, comment and subscribe! That's what keeps me going. Feel free to support me on Patreon: https://www.patreon.com/user?u=3191693 Two Minute Papers Link: https://www.youtube.com/playlist?list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 250829 Siraj Raval
Tutorial: Bitcoin News Sentiment Analysis in Python
 
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It's very obvious that the major news have had a big influence on Bitcoin price. Analyzing them can provide an insight of the future trend. In this video tutorial, we will use TextBlob library which makes natural language processing very quick and easy. Moreover, instead of getting the articles by web scraping, we'll use an API. Anaconda: https://www.anaconda.com/download/ NewsAPI: https://newsapi.org/ TextBlob: documents: http://textblob.readthedocs.io/en/dev/
Views: 471 Python for Trading
How to do real-time Twitter Sentiment Analysis (or any analysis)
 
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This tutorial video covers how to do real-time analysis alongside your streaming Twitter API v1.1 feed. In this case, for example, we use the Sentdex Sentiment Analysis API, http://sentdex.com/sentiment-analysis-api/, though you can use ANY API like this, or just your own custom function too. If you don't already have a twitter stream set up, here is some sample code and tutorial video for it: http://sentdex.com/sentiment-analysisbig-data-and-python-tutorials-algorithmic-trading/how-to-use-the-twitter-api-1-1-to-stream-tweets-in-python/ Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 70180 sentdex
Reading Bitcoin Sentiment | Three Stages
 
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The second video in my sentiment reading series. This video covers the three stages of an uptrend and how to buy at market bottoms and sell at market tops within stage 3 of a trend. Sentiment Cheat Sheet: https://goo.gl/6gdtUr Timestamps: Three Stages Theory: 1:22 First Example: 3:11 Second Example: 5:12 Third Example: 7:22 Where will BTC go - test: 9:54 Join Coinbase with this referral code for $10 free of Bitcoin after making a trade of $100 or more! : https://www.coinbase.com/join/5a261777dce5a8011ba23007 Suggest a video on Patreon: https://www.patreon.com/BitcoinTradingChallenge Site used: https://www.bfxdata.com/positions/btcusd An even better Sentiment Provider than BFXdata: https://datamish.com/dashboard/db/btcusd?refresh=10s&orgId=1 The Platform I use to Trade - https://exchange.gemini.com/ The Website I use for Analysis - https://cryptowat.ch/gemini/btcusd My Discord Chat: https://discord.gg/MSrNkbg _________________________________________________________________________________________________ Disclaimer: The content covered in this video is NOT investment advice and I am not a financial advisor. The material covered within these videos is for educational purposes only. Always do your own research and only invest based on your own findings and personal judgment. Happy Trading!
Sentiment Analysis in Python with TextBlob and VADER Sentiment (also Dash p.6)
 
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What's going on everyone and welcome to a quick tutorial on doing sentiment analysis with Python. Today, I am going to be looking into two of the more popular "out of the box" sentiment analysis solutions for Python. The first is TextBlob, and the second is going to be Vader Sentiment. Text tutorials and sample code: https://pythonprogramming.net/sentiment-analysis-python-textblob-vader/ Reviews files: https://pythonprogramming.net/static/downloads/short_reviews/ Discord: https://discordapp.com/invite/3jCqXJj Support the content: https://pythonprogramming.net/support-donate/ Twitter: https://twitter.com/sentdex Facebook: https://www.facebook.com/pythonprogramming.net/ Twitch: https://www.twitch.tv/sentdex G+: https://plus.google.com/+sentdex
Views: 20605 sentdex
Twitter Sentiment Analysis Using TWEEPY
 
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Twitter is a popular microblogging service where users create status messages (called "tweets"). These tweets sometimes express opinions about different topics. The purpose of this project is to build an algorithm that can accurately classify Twitter messages as positive or negative, with respect to a query term. Our work is that we can obtain high accuracy on classifying sentiment in Twitter messages using machine learning techniques. Generally, this type of sentiment analysis is useful for consumers who are trying to research a product or service, or marketers researching public opinion of their company.
Views: 195 RAHUL SHARMA
Twitter Sentiment Analysis Demo
 
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Our team created an NLP demo for two European banks interested to conduct real-time sentiment analysis of textual data at scale. This demo addresses and illustrates two separate engineering challenges: 1) Building an NLP model that achieves near state-of-art results in sentiment analysis 2) Building a high-performant and scalable data pipeline that utilizes the model and provides real-time analytics over twitter data Even though the demo has been tailored to Twitter data at present, the underlying approach can be applied to any textual dataset – e.g., Facebook feeds, news feed, user reviews, comments, etc. As a result, this approach is applicable to and renders significant value across various domains.
Views: 591 Centroida Official
Sentiment Analysis with Python and TextBlob
 
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In this video, I'm discussing the use of Python and TextBlob to get a rudimentary assessment of user sentiment on a particular subject. As luck would have it, others have already beat me to it. I'll link to someone's work on this exact subject matter: https://www.geeksforgeeks.org/twitter-sentiment-analysis-using-python/ My code can be found on LinkedIn: https://www.linkedin.com/pulse/twitter-sentiment-analysis-python-brian-warner/ If you're interested in machine learning and taking some courses online, I recommend: Data Camp: https://www.datacamp.com Data Quest: https://www.dataquest.io Coursera: https://www.coursera.org Udacity: https://www.udacity.com You can also check out "Udemy.com" but I can't vouch for the courses there (haven't taken any yet.) If interested, you can search for more on this topic by looking up: "Deep Learning" "Machine Learning" "AI"
Views: 1133 Brian Warner
Sentiment Analysis on Twitter Data
 
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IRE Project under Guidence of Vasudeva Varma nd Lokesh Walase-- Created using PowToon -- Free sign up at http://www.powtoon.com/youtube/ -- Create animated videos and animated presentations for free. PowToon is a free tool that allows you to develop cool animated clips and animated presentations for your website, office meeting, sales pitch, nonprofit fundraiser, product launch, video resume, or anything else you could use an animated explainer video. PowToon's animation templates help you create animated presentations and animated explainer videos from scratch. Anyone can produce awesome animations quickly with PowToon, without the cost or hassle other professional animation services require.
Views: 198 balu selva
Stock prediction using sentimental analysis - BE IT Final Year Project 2017
 
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Stock prediction using sentimental analysis - BE IT Final Year Project 2017
Presentation Analyse de sentiments
 
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-- Created using PowToon -- Free sign up at http://www.powtoon.com/youtube/ -- Create animated videos and animated presentations for free. PowToon is a free tool that allows you to develop cool animated clips and animated presentations for your website, office meeting, sales pitch, nonprofit fundraiser, product launch, video resume, or anything else you could use an animated explainer video. PowToon's animation templates help you create animated presentations and animated explainer videos from scratch. Anyone can produce awesome animations quickly with PowToon, without the cost or hassle other professional animation services require.
Views: 324 kent AQUEREBURU
Python and Pandas for Sentiment Analysis and Investing 2 - Pandas Basics
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share This video tutorial is dedicated to teaching the basics of using Pandas with Python. In this example we grab stock prices from Yahoo Finance, learn how to access specific columns, how to modify columns, add columns, delete columns, and perform basic math on them. This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas is used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Matplotlib Styles video: https://www.youtube.com/watch?v=WmhdQdx8Gjo Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 13647 sentdex
Topic Modeling & Sentiment Analysis on News Articles and Comments
 
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Topic Modeling and Constructiveness/Toxicity/Sentiment Analysis in New Articles and Comments by using the SFU Opinion and Comments Corpus (SOCC) dataset, which contains articles and comments for 5 years from 2012 to 2016. The motivation for our project is to create a succinct summary of different views or opinions among Canadian citizens on articles, issues, or policies to help the Canadian government or organizations to make better decisions.
Views: 141 Ruoting Liang
Sentiment Analysis
 
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This is an extract of our Advanced Technical Analysis Course. This originally designed Forex.Academy course is our response to the important role that technical analysis plays in today’s understanding of financial markets. It is in fact so relevant that Forex.Academy dedicates 2 entire sections to please enthusiastic technicists, i.e., Charting and Crypto & ICO Charting. However, mastering technical analysis is anything but easy. After recognising the scattered nature of all sources of technical classifications, in this course we break down many of the pros and cons associated with each type of technical approach leaving you with the ability to make your own decisions when it comes to technical trading. Becoming an expert “chartist” is the first step of the Forex.Academy´s exclusive Educational Trilogy, also consisting of the Live Beginner’s Course, and the Become a Pro Course PLUS service. Subscribe to our channel to receive our educational videos and if you like your likes they are very appreciated and will help us grow. All our services (live-trading sessions, educational signals, training courses, market update, social media & libraries on different formats) on our website: https://forex.academy You can also follow us on: Twitter: @ForexAcademyPro Facebook Group: https://www.facebook.com/groups/forex.crypto.academy/
Views: 67 Forex Academy
Real-Time Sentiment Analysis on Cryptocurrency Using Tweets
 
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Performing a real-time sentiment analysis on cryptocurrency in Python
Views: 92 Zach Yaldo
A Sentiment Analysis App Built on IBM Watson... WatermelonBlock Review
 
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In today's sponsored video, we review the sentiment analysis app WaterMelonBlock. Head to: https://www.watermelonblock.io For ICO details: https://ico.watermelonblock.io/ Get a 14-day trial for only $7 at https://www.signalprofits.com today! A leader in market updates, short, medium and long term trading signals. JOIN THE COMMUNITY 👋 ILoveCrypto Facebook Group: https://www.facebook.com/groups/ILoveCrypto 🚀 Become a VIP Signal Profits Member: http://bit.ly/2J5AK71 WE DO SOCIAL 📒 Facebook: https://www.facebook.com/JakeCanfield/ 🐦 Twitter: https://www.twitter.com/ILoveCrypt0 🐦 Twitter: https://twitter.com/StrongHandsHODL 📷 Instagram: https://www.instagram.com/ILoveCrypto RESOURCES Best Wallets: Ledger Wallet - http://bit.ly/LedgerNanoWallets Trezor Wallet - http://bit.ly/TrezorHardwareWallet Best Exchanges: Binance: https://www.binance.com/?ref=11661178 Kucoin: https://www.kucoin.com Best Trading Software: Trading View: http://bit.ly/TradingViewSoftware Coinigy: http://bit.ly/CoinigyTrading 💥 Best Research: Research Profits: https://research.signalprofits.com/investor-profits 🔍 DYOR Guide: https://research.signalprofits.com/investor-profits My Sponsor: For absolute protection while trading cryptocurrencies, make sure you pick up a CryptoWall at https://www.cryptowall.ca and use the discount code “ILOVECRYPTO” for 5% off your purchase. Cryptowall doesn’t allow anybody to get into your network, including malware. Disclaimer: I am a Certified Bitcoin Professional licensed by the Cryptoconsortium but I am NOT a financial advisor, and nothing I say is meant to be a recommendation to buy or sell any financial instrument. I will NEVER ask you to send me money to trade for you. Please report any suspicious emails or fake social media profiles claiming to be me. Don't invest money you can't afford to lose. There are no guarantees or certainties in trading. My videos may contain affiliate links or sponsorships to products I believe will add value to your life and help you in trading. No matter what I or anyone else says, it’s important to do your own research before making a financial decision involving cryptocurrencies.
Views: 5240 I Love Crypto
Python Web Scraping & Sentiment Analysis Tutorial For Beginners | Top 100  Subreddits
 
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Learn how to scrape the web and analyze sentiment using python and bs4 with TextBlob, also learn how to use the PRAW python reddit API. ► 1:1 Mentorship: https://goo.gl/P3PgC2 Code: https://github.com/jg-fisher/redditSentiment If you enjoyed this video, I would really appreciate it if you subscribed below, thanks! Also, be sure to leave any questions or feedback in the comments section.
Views: 9593 John G. Fisher
News Sentiment Analysis and Stock Selection Strategies
 
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Slides available ► https://goo.gl/rs3ZTT Full Event ► https://goo.gl/LvnmwY Gordon Ritter - Senior Portfolio Manager - GSA Capital Lakonishok and Lee (2001) examine whether company insiders earn abnormal returns from their purchasing activity. Similarly Ikenberry, Lakonishok, and Vermielen (1995) investigate whether companies that announce open market share repurchase programs earn abnormal returns in subsequent years. It makes sense to view both kinds of activity in a unified way, as both are indicative of positive sentiment by agents (such as corporate directors) who have a clear informational advantage over other market participants. In the present work we re-examine this classic anomaly in a modern context, by utilizing a real-time news feed from Ravenpack to identify insider transactions and open-market share repurchase programs. We discuss how to recast “insider sentiment news” as a factor in a multifactor model in the style of Ross’ APT, and go on to study the associated Markowitz portfolios. Using this data set as an example, we discuss the generally-interesting problem of computing Markowitz portfolios for many thousands of assets in a numerically stable and computationally efficient manner. Recent work of the author proves that the computational complexity of Markowitz optimization in the context of an APT model scales linearly with the number of assets, and gives an explicit formula for performing such linear-time computations. The explicit formula admits easy implementation in any modern programming language, and can optimize portfolios of many thousands of assets in a few milliseconds on a laptop computer. Session recorded June 16, 2016 at the RavenPack 4th Annual Research Conference, titled "Reshaping Finance with Alternative Data". Watch all sessions: ► https://goo.gl/3ij1Ev Visit us at ►https://www.ravenpack.com/ Follow RavenPack on Twitter ► https://twitter.com/RavenPack
Views: 1002 RavenPack
Python Projects 1: Newspaper Sentiment analysis
 
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Hey there guys and gals! It's Mr.ThunderGod here with some Thunder Code! Presenting the Newspaper Sentiment analysis-inator! This little script downloads and analyzes newspaper articles to find if they are positive, negative or neutral! Github Link: https://github.com/mrthundergod/Newspaper-Sentiment-Analysis If you have doubts, comment below!!
Views: 449 MrThunderGod
How to predict Bitcoin price ( Time Series ) using LSTM Recurrent Neural Network | Sudharsan
 
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In this tutorial, Let us understand how to predict bitcoins price ( Time series analysis ) using long short term memory recurrent neural network. Code for this video: https://github.com/sudharsan13296/Bitcoin-price-Prediction-using-LSTM Follow me on twitter: https://twitter.com/sudharsan1396
Python and Pandas for Sentiment Analysis and Investing 6 - Basics for a Strategy
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas is used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ Matplotlib Styles video: https://www.youtube.com/watch?v=WmhdQdx8Gjo http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 3144 sentdex
Random Forest Classifier for News Articles Sentiment Analysis
 
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Introduction DATA MINING It is the process to discover the knowledge or hidden pattern form large databases. The overall goal of data mining is to extract and obtain information from databases and transfer it into an understandable format for use in future. It is used by Business intelligence organizations, Financial analysts, Marketing organizations, and companies with a strong consumer focus like retail ,financial and communication . It can also be seen as one of the core process of knowledge discovery in data base (KDD). It can be viewed as process of Knowledge Discovery in database. Data Extraction/gathering:- To collect the data from sources . Eg: data warehousing. Data cleansing :- To eliminate bogus data and errors. Feature extraction:- To extract only task relevant data : i.e to obtain the interesting attributes of data . Pattern extraction and discovery :- This step is seen as process of data mining , where one should concentrate the effort. Visualization of the data and Evaluation of results :- To create knowledge base. CLASSIFICATION Classification is a technique of data mining to classify each item into predefined set of groups or classes. The goal of classification is to accurately predict the target class for each item in the data. For example, a classification model could be used to identify loan applicants as low, medium, or high credit risks. The simplest type of classification problem is binary classification. In binary classification, the target attribute has only two possible values: for example, high credit rating or low credit rating. Multiclass targets have more than two values: for example, low, medium, high, or unknown credit rating. SENTIMENT ANALYSIS Sentiment analysis is a sub-domain of opinion mining where the analysis is focused on the extraction of emotions and opinions of the people towards a particular topic. Sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic. The attitude may be his or her judgment or evaluation, affective state (that is to say, the emotional state of the author when writing), or the intended emotional communication (that is to say, the emotional effect the author wishes to have on the reader). With opinion mining, we can distinguish poor content from high quality content. Random Forest Technique In this technique, a set of decision trees are grown and each tree votes for the most popular class, then the votes of different trees are integrated and a class is predicted for each sample. This approach is designed to increase the accuracy of the decision tree, more trees are produced to vote for class prediction. This approach is an ensemble classifier composed of some decision trees and the final result is the mean of individual trees results. Follow Us: Facebook : https://www.facebook.com/E2MatrixTrainingAndResearchInstitute/ Twitter: https://twitter.com/e2matrix_lab/ LinkedIn: https://www.linkedin.com/in/e2matrix-thesis-jalandhar/ Instagram: https://www.instagram.com/e2matrixresearch/
Distantly Supervised Lifelong Learning for Large-Scale Social Media Sentiment Analysis
 
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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:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/clickmyproject Mail Us: [email protected]
Views: 65 Clickmyproject
Python and Pandas for Sentiment Analysis and Investing 12
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas is used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 2660 sentdex
Trade The Sentiment Overview
 
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An overview of the Trade The Sentiment service. Trade The Sentiment performs sentiment analysis on Twitter Messages and then provides a quantitative signal that can be used to inform investing decisions in the stock market. Join us at http://tradethesentiment.com.
Views: 614 Trade The Sentiment
Python and Pandas for Sentiment Analysis and Investing 4 - Data manipulation
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share In this video, we learn how to access specific data from our dataset. This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas is used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ Matplotlib Styles video: https://www.youtube.com/watch?v=WmhdQdx8Gjo http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 5056 sentdex
Unsupervised Machine Learning - Flat Clustering with KMeans with Scikit-learn and Python
 
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This unsupervised machine learning tutorial covers flat clustering, which is where we give the machine an unlabeled data set, and tell it how many categories we want the data categorized into. sample code: http://pythonprogramming.net http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 47949 sentdex
Python and Pandas for Sentiment Analysis and Investing 10 - testing
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas is used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 2108 sentdex
Python and Pandas for Sentiment Analysis and Investing 3 - Looking at our Data
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas is used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ Matplotlib Styles video: https://www.youtube.com/watch?v=WmhdQdx8Gjo http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 6327 sentdex
Python and Pandas for Sentiment Analysis and Investing 11
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share Stocklist for this video: http://sentdex.com/sentiment-analysis-tutorial-documents/ This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas is used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 1950 sentdex
Demo Sentiment Analysis of given text & deployment in Django Application
 
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Sentiment Analysis of given text & deployment in Django Application || Demo with NLTK and Django
Views: 92 raja p
A Machine Learning-Based Trading Strategy Using Sentiment Analysis Data
 
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Slides available ► https://goo.gl/1Xc3fJ Full Event ► https://goo.gl/ucxU1S Watch all sessions: ► https://goo.gl/LrMFPA Tucker Balch - Co-Founder & CTO - Lucena Research. In this talk, Tucker shows how sentiment information in combination with a Machine Learning technique can provide a successful stock trading strategy. Specifically, he creates a predictive Machine Learning-based model for company stock prices based on the recent sentiment data; he uses that model as an input to build portfolios that are re-balanced weekly and simulate the performance of those portfolios. His results indicate that the sentiment information has predictive value and is useful as part of a Machine Learning strategy that significantly outperforms the market from which the candidate equities are drawn. Presentation held at 3rd Annual RavenPack Research Symposium entitled "Big Data Analytics for Alpha, Smart Beta & Risk Management". Visit us at ►https://www.ravenpack.com/ Follow RavenPack on Twitter ► https://twitter.com/RavenPack
Views: 10500 RavenPack
It's Official! Did the NSA Create Bitcoin? That's Classified!
 
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Silver Shield Merchandise https://teespring.com/stores/silver-shield Silver Shield MiniMintage https://www.goldenstatemint.com/Silver-shield-collection/ JOIN MY EMAIL LIST (before I get banned) https://www.mcssl.com/WebForms/WebForm.aspx?wid=756241a9-27b7-4106-b0cb-c685a5a68afc Silver Shield Group MicroMintage https://silvershieldxchange.com/2016/07/28/join-silver-shield-group/ DONATE! https://www.paypal.me/SilverShieldXchange Silver Shield Guide http://www.silvershieldguide.com/ FREE 46 HOUR Sons of Liberty Academy http://sonsoflibertyacademy.com TWITTER @SilverShield76 INSTAGRAM @SilverShieldXchange
Views: 8036 TruthNeverTold
Reinforcement Learning for Stock Prediction
 
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Can we actually predict the price of Google stock based on a dataset of price history? I’ll answer that question by building a Python demo that uses an underutilized technique in financial market prediction, reinforcement learning. The specific technique we'll use in this video is a subset of RL called Q learning. Using a combination of code, animations, and theory i'll explain how we can let our AI learn a policy for when to buy and sell google stock to maximize profit. Code for this video: https://github.com/llSourcell/Reinforcement_Learning_for_Stock_Prediction Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology This video is apart of my Machine Learning Journey course: https://github.com/llSourcell/Machine_Learning_Journey More Learning Resources: http://cs229.stanford.edu/proj2006/Molina-StockTradingWithRecurrentReinforcementLearning.pdf http://www.wildml.com/2018/02/introduction-to-learning-to-trade-with-reinforcement-learning/ https://medium.com/@ranko.mosic/predicting-price-movement-and-trading-using-reinforcement-learning-kearns-nevmyvaka-2013-b5a64daa34f0 https://hub.packtpub.com/develop-stock-price-predictive-model-using-reinforcement-learning-tensorflow/ https://iknowfirst.com/deep-reinforcement-learning-part-2-the-game-of-stock-trading https://www.youtube.com/watch?v=v_L9jR8P-54&list=PLQVvvaa0QuDe6ZBtkCNWNUbdaBo2vA4RO Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Sign up for the next course at The School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 35016 Siraj Raval
Python and Pandas for Sentiment Analysis and Investing 9 - Mapping Function to Dataframe
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas is used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ Matplotlib Styles video: https://www.youtube.com/watch?v=WmhdQdx8Gjo http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 2157 sentdex
Sentiment Analysis in Python with TextBlob
 
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In This Video I Will Show You How TextBlob Work To Find Sentiment Analysis Sentiment Analysis in Python with TextBlob
Views: 32 TechHub
Towards Real-Time, Country-Level Location Classification of Worldwide Tweets
 
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Towards Real-Time, Country-Level Location Classification of Worldwide Tweets To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83.Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #37, Kamaraj Salai,Thattanchavady, Puducherry -9.Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690, Email: [email protected], web: http://www.jpinfotech.org The increase of interest in using social media as a source for research has motivated tackling the challenge of automatically geolocating tweets, given the lack of explicit location information in the majority of tweets. In contrast to much previous work that has focused on location classification of tweets restricted to a specific country, here we undertake the task in a broader context by classifying global tweets at the country level, which is so far unexplored in a real-time scenario. We analyse the extent to which a tweet’s country of origin can be determined by making use of eight tweet-inherent features for classification. Furthermore, we use two datasets, collected a year apart from each other, to analyse the extent to which a model trained from historical tweets can still be leveraged for classification of new tweets. With classification experiments on all 217 countries in our datasets, as well as on the top 25 countries, we offer some insights into the best use of tweet-inherent features for an accurate country-level classification of tweets. We find that the use of a single feature, such as the use of tweet content alone – the most widely used feature in previous work – leaves much to be desired. Choosing an appropriate combination of both tweet content and metadata can actually lead to substantial improvements of between 20% and 50%. We observe that tweet content, the user’s self-reported location and the user’s real name, all of which are inherent in a tweet and available in a real-time scenario, are particularly useful to determine the country of origin. We also experiment on the applicability of a model trained on historical tweets to classify new tweets, finding that the choice of a particular combination of features whose utility does not fade over time can actually lead to comparable performance, avoiding the need to retrain. However, the difficulty of achieving accurate classification increases slightly for countries with multiple commonalities, especially for English and Spanish speaking countries.
Views: 415 jpinfotechprojects
Scikit Learn Machine Learning SVM Tutorial with Python p. 2 -  Example
 
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In this machine learning tutorial, we cover a very basic, yet powerful example of machine learning for image recognition. The point of this video is to get you familiar with machine learning in Python with sklearn, but also to show you that the actual machine learning part is the easy part. Playlist link: https://www.youtube.com/watch?v=URTZ2jKCgBc&list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3&index=2 The real hard part is everything else. Getting data, organizing data, labeling data, scaling data.... and more. sample code: http://pythonprogramming.net http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 221049 sentdex
Automated Web Scraping in R: Writing your Script
 
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In this video tutorial you will learn how to write standard web scraping commands in R, filter timely data based on time diffs, analyze or summarize key information in the text, and send an email alert of the results of your analysis. Packages used: rvest - for downloading website data lubridate - for cleaning, converting date-time data stringr - for cleaning text in r LSAfun - for ranking/summarizing the text Recommended for medium level R users. See our Introduction to R to get up-to-speed with basic R commands: https://tutorials.datasciencedojo.com/introduction-to-r/ The R full script for this video tutorial can be accessed here: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/web_scraping_R-master Link to Website used: https://www.marketwatch.com/story/bitcoin-jumps-after-credit-scare-2018-10-15 To see an example of web scraping timely political news events and commentary from Reddit, check out Data Science Dojo's blog tutorial on KDnuggets: https://www.kdnuggets.com/2018/12/automated-web-scraping-r.html -- 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/H0fZy3C0 See what our past attendees are saying here: https://hubs.ly/H0fZyph0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 952 Data Science Dojo
Sentiment Analysis in Real Time for Twitter, Reddit and News (Beta Test)
 
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Ask for beta key: [email protected] Check out SvejkAnalytics: http://www.svejkanalytics.com Written in Python and C our software is able to analyze the emotions of Tweets, Reddit posts and News articles. The site will go public till December, but you can message me for a beta key. We are also looking for programmers. Currently the team is two developers, one C and one Python dev. You can also find link to our Slack channel on the website.
Views: 69 Márk Ibolya
Python and Pandas for Sentiment Analysis and Investing 5 - Removing Outlier Data Plots
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share In this video, we cover how to remove outliers with pandas and standard deviation. This series uses python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas is used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ Matplotlib Styles video: https://www.youtube.com/watch?v=WmhdQdx8Gjo http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 6100 sentdex
CMU 15388 Final - Stock Market Prediction Using Sentiment Analysis
 
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15388 Final Project presentation
Views: 214 sam1323123
Visualisation: Political Tweets and Twitter Trending
 
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Visualisation: Political Tweets and Twitter Trending My Bitcoin address if you so wish to support my work: 3BeNHRSMjr7iJKRhfyosJWXR11HFvxeZMp Follow me on Twitter: @drecuk @eugenechngart Website: http://www.complexity.io YouTube: http://www.youtube.com/genechng
Views: 149 Eugene Ch'ng
Scikit Learn Machine Learning Tutorial for investing with Python p. 16
 
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In this machine learning tutorial video, we cover how to add data from another data set, Quandl, to our existing set. sample code: http://pythonprogramming.net http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 14026 sentdex
Stock Market Prediction
 
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Can we predict the price of Microsoft stock using Machine Learning? We'll train the Random Forest, Linear Regression, and Perceptron models on many years of historical price data as well as sentiment from news headlines to find out! Code for this video: https://github.com/llSourcell/Stock_Market_Prediction Please Subscribe! And like. And comment. That's what keeps me going. Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://www.quantinsti.com/blog/machine-learning-trading-predict-stock-prices-regression/ https://medium.com/@TalPerry/deep-learning-the-stock-market-df853d139e02 https://iknowfirst.com/rsar-machine-learning-trading-stock-market-and-chaos https://www.udacity.com/course/machine-learning-for-trading--ud501 https://quant.stackexchange.com/questions/111/how-can-i-go-about-applying-machine-learning-algorithms-to-stock-markets https://quant.stackexchange.com/questions/111/how-can-i-go-about-applying-machine-learning-algorithms-to-stock-markets http://eugenezhulenev.com/blog/2014/11/14/stock-price-prediction-with-big-data-and-machine-learning/ https://cloud.google.com/solutions/machine-learning-with-financial-time-series-data https://www.linkedin.com/pulse/deep-learning-stock-price-prediction-explained-joe-ellsworth If you're wondering why my voice sounds weird, it's because i was down with Traveler's Diarrhea from my recent trip to India. It's such a debilitating sickness, but the show must go on. And yes, thankfully I'm better now :) Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 76703 Siraj Raval
Opinion Mining - Restaurant Reviews
 
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-- Created using PowToon -- Free sign up at http://www.powtoon.com/youtube/ -- Create animated videos and animated presentations for free. PowToon is a free tool that allows you to develop cool animated clips and animated presentations for your website, office meeting, sales pitch, nonprofit fundraiser, product launch, video resume, or anything else you could use an animated explainer video. PowToon's animation templates help you create animated presentations and animated explainer videos from scratch. Anyone can produce awesome animations quickly with PowToon, without the cost or hassle other professional animation services require.
Views: 1120 Suraj Bennur
Python and Pandas for Sentiment Analysis and Investing 1 - Download and Installing
 
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Full Python + Pandas + Sentiment analysis Playlist: http://www.youtube.com/watch?v=0ySdEYUONz0&list=PLQVvvaa0QuDdktuSQRsofoGxC2PTSdsi7&feature=share Welcome to the introduction video for my Python and Pandas for sentiment analysis and investing series. This series will be using python with Pandas for data analysis. Our data set will be a database dump from Sentdex.com sentiment analysis, containing about 600 stocks, mostly S&P 500 stocks. Pandas will be used to work with our data quickly and efficiently. The ideas of Pandas is to act as a sort of framework for quickly analyzing data and modeling it. Sentiment Analysis data: http://sentdex.com/downloads/stocks_sentdex.csv.gz Python Module downloads: (Get all of the listed dependencies, or at least the major ones like NumPy, Dateutils, Matplotlib, ) http://www.lfd.uci.edu/~gohlke/pythonlibs/#pandas https://www.python.org/downloads/ http://matplotlib.org/downloads.html http://www.numpy.org/ http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Views: 22043 sentdex
Understanding Customer Sentiments Using Social Media
 
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Sentiment in this context means opinions—and people have them. It is natural for humans to have them about what they observe and experience. It is critical for businesses to measure the sentiments of their customers in order for them to create the products and provide services their customers like. But “sentiment” is very challenging to measure with precision. Twitter is one compelling resource to help you measure your customer’s opinions. By analyzing tweets, you can determine and measure the sentiments of your prospects and customers. Dr. Ash Pahwa, Ph.D., is an educator, author, entrepreneur, and technology visionary with three decades of industry and academic experience. He will introduce you to the field of Sentiment analysis and provide practical tips on how you can start keeping track of and measuring your customers’ interests and needs using social media.

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