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Udemy - Applied Text Mining And Sentiment Analysis With Python
TORRENT SUMMARY
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Perform Sentiment Analysis on Twitter data by combining Text Mining and NLP techniques, NLTK and Scikit-Learn
What you'll learn:
How to use common Text Mining and NLP techniques
How to use Regex to clean up Tweets
How to use NLTK to pre-process text
How to use Scikit-Learn to build a Sentiment Analysis prediction model
How to predict the sentiment of any tweet
Requirements
A basic Python IDE (Spyder, Pycharm, etc.) or a web-based Python IDE (Jupyter Notebook, Google Colab, etc.). Google Colab will be used by default to teach this course.
General knowledge of Python, as this is a course about learning Sentiment Analysis and Text Mining, not properly about learning Python.
Description
"Bitcoin (BTC) price just reached a new ALL TIME HIGH! #cryptocurrency #bitcoin #bullish"
For you and me, it seems pretty obvious that this is good news about Bitcoin, isn't it? But is it that easy for a machine to understand it? ... Probably not ... Well, this is exactly what this course is about: learning how to build a Machine Learning model capable of reading and classifying all this news for us!
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