This project aims to build a generic Machine Learning framework/pipeline to preform Sentiment Analysis in Python and R.

1. Data Set
   • Get Train and Test datasets
2. Feature Engineering
   • Removing stop words
   • Stemming and lemmatization
   • Bag of Words model - Count Vectorizer, TF-IDF
3. Model Building
   • Random Forest
   • AdaBoost
   • Logistic Regression
   • Naive-Bayes
   • SVM Classifier
   • Neural Network
4. Model Stacking
5. Model Evaluation

• Finish front-end flask app UI
• Finish Model building
• Finish Model Stacking
• Finish front-end flask app functionality

For any suggestion/clarification please contact me at kirankunapuli.github.io