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Machine learning and Lexicon approach to Sentiment analysis

Machine learning and Lexicon based approach to Sentiment analysis using Twitter API

4.45 / 5.0
5933 students3 hours 25 minutes

Created by Jaro Algo, offered on Udemy

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Overall score


This course currently has a bestcourses score of 6.5/10, which makes it an average course. Overall, there are probably better courses available for this topic on our platform.


Learn how to connect and download tweets through Twitter API. From there I will show you how to clean this data and prepare them for sentiment analysis. There are two most commonly used approaches to sentiment analysis so we will look at both of them. First one is Lexicon based approach where you can use prepared lexicons to analyse data and get sentiment of given text. Second one is Machine learning approach where we train our own model on labeled data and then we show it new data and hopefully our model will show us sentiment. At the end you will be able to build your own script to analyze sentiment of hundreds or even thousands of tweets about topic you choose.

What you will learn

  • How to create twitter developer account and connect to twitter API
  • Download Tweets, clean and store them in to Pandas DataFrame
  • Learn about Tokenization, Lemmatization, Stemming and much more
  • Perform Sentiment analysis with Vader and TextBlob lexicons
  • Learn about Machine learning approach to Sentiment Analysis
  • Build and test machine learning models


  • Basic Python knowledge (I explain each step so you can understand what I am doing)
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Frequently asked questions

  • Price: $19.99
  • Platform: Udemy
  • Language: English
  • 3 hours 25 minutes
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bestcourses score: 6.5/10

There might be better courses available for this topic.