Sentiment analysis is an important part of NLP  that identifies the emotional tone behind a body of text and is used in customer reviews and survey responses, online and social media. In this project, you will determine the sentiment of movie reviews as positive, negative, and neutral. We start off with a rule-based method, then use Machine Learning, explaining the connection between the two. You will use Pandas to load, analyze and process your data.  Then use sklearn to transform your data with Bag-Of-Words, or Term Frequency–Inverse Document Frequency transforms, then find the  Sentiment using   Machine Learning. Streamline the process apply Machine learning pipelines, and perform  Hyperparameter selections in one shot. Finally, use libraries like the Natural language tool kit to improve performance. Each section will have toy examples so you can better wrap your head around it.

You will need to know how to program in  Python and be somewhat familiar with Pandas and sklearn and logistic regression.