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:
- Noise Removal
- Lexicon Normalization
- Lemmatization
- Stemming
- Object Standardization
- Syntactical Parsing
- POS Tagging
- Entity Parsing
- Topic Modelling(LDA)
- Bi-Grams
- Statistical features
- TF – IDF
- Text Classification
- TextBlob with naive bayes
- Sklearn with SVM
- 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