Basic Guide to NLP

This repository contains a Jupyter notebook with sample python codes for basic to major NLP problems faced when dealing with text. There's one more repo specifically based on NLTK library for NLP tasks https://github.com/akanshajainn/NLTK-with-Python3

All the codes are successfully runnning in python 3 as of now.

Following are the topics included:

1. Noise Removal
2. Lexicon Normalization
   • Lemmatization
   • Stemming
3. Object Standardization
4. Syntactical Parsing
   • POS Tagging
5. Entity Parsing
   • Topic Modelling(LDA)
   • Bi-Grams
6. Statistical features
   • TF – IDF
7. Text Classification
   • TextBlob with naive bayes
   • Sklearn with SVM
8. Text Matching
   • Levenshtein Distance
   • Phonetic Matching
   • Cosine Similarity

PS. It is inspired from an article on Analytics Vidhya written by Shivam Bansal. Link: https://www.analyticsvidhya.com/blog/2017/01/ultimate-guide-to-understand-implement-natural-language-processing-codes-in-python/#comment-151409