Machine learning and Lexicon approach to Sentiment analysis

MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 23 lectures (3 hour, 25 mins) | Size: 1.53 GB
Learn how to connect and tweets through Twitter API.
What you'll learn
How to create twitter developer account and connect to twitter API
Tweets, clean and store them in to Pandas DataFrame
Learn about Tokenization, Lemmatization, Stemming and much more
Perform Sennt analysis with Vader and TextBlob lexicons
Learn about Machine learning approach to Sennt Analysis
Build and test machine learning models
Requirements
Basic Python knowledge (I explain each step so you can understand what I am doing)
Description
From there I will show you how to clean this data and prepare them for sennt analysis. There are two most commonly used approaches to sennt 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 sennt 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 sennt. At the end you will be able to build your own script to analyze sennt of hundreds or even thousands of tweets about topic you choose.
Who this course is for:
Bner Python developers curious about data science
Anyone who is interested in data analysis
People who wants to include sennt analysis for their projects
DOWNLOAD
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https://uploadgig.com/file/download/A4F7dbc9206CBbe1/62N5WjDk_.Machine_le.part2.rar
rapidgator
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