Implementation of various basic text analytics techniques and algorithms.
- Data Scraping
- Normalization/Preprocessing
- Tokenization
- Vectorization: Feature Extraction
- Bag of Words
- TF-IDF
- Unsupervised Learning:
- Document Similarity
- Cosine Similarity
- Document Clustering Algorithms
- Document Similarity
- Supervised Learning:
- Classification Algorithms
- Word Clouds - simple term freq distribution of using NLTK and Word_Cloud library. (data: Gutenberg Project)