Twitter Data Sentiment Analysis

This repository was stored some code in ipynb files. The ipynb contain a code for classifying sentiment analysis for twiiter data.
The Feature extraction that are used in ipynb:

1. TF-IDF Vectorizer
2. Countvectorizer
3. Hashing Vectorizer
4. Bigram Vectorizer

The classifier that are used in ipynb:

1. Logistic Regression
2. Multinomial Naive Bayes

The pdf was a documentation of implementation sentiment analysis for twitter data using Spark with pyspark2.