Repository containing portfolio of NLP projects completed by me for academic, self learning, and hobby purposes. Presented in the form of iPython Notebooks.

Tools : NLTK, scikit-learn

Used a logistic regression, naive bayes and SVM classifier, bag-of-words features, and polarity lexicons (both in-built and external). We'll also create our own UDF to clean raw text present in the form of reviews.

• Review in the form of free text was scrapped and the user rating
• A user rating of 1,2,3 -> sentiment 0 -> negative sentiment
• A user rating of 4 and 5 -> sentiment 1 -> positive sentiment

1. Getting some visuals on text data
   • Wordcloud
   • bargraph
   • Frequency graph
2. Text cleaning tasks
3. Extarct features from text and convert text to numbers
4. n-gram analysis -> bigram, trigrams, obtain visuals on the n-grams
5. Sentiment analysis using AFFIN and VADER
6. Document classification
7. Document clustering
8. Document and word similarlity