Preliminary Table of Content

NLTK

1. Introduction to NLTK
2. Lemmatising and stemming words
3. Training a simple occurrence based tagger
4. Bigrams and Trigrams
5. Finding collocations

Scikit-Learn

1. Text Classification with NaiveBayes
2. Text Clustering
3. Displaying text in 2D with t-SNE
4. Building a POS Tagger using a SVM model
5. Building a NER using CRFSuite
6. Building a POS tagger using Pomegranate

Gensim

1. Building an LDA Topic model
2. Extracting collocations with the Phrase model
3. Training a Word2Vec model
4. Text summarisation with TextRank

spaCy

1. Introduction to spaCy
2. Visualising dependency trees
3. Training your NER
4. Adding new language support

Keras

1. Building a DNN for Sentiment Analysis
2. Building an RNN for sentiment Analysis
3. Building an RNN for POS Tagging
4. Transfer Learning using pretrained word vectors
5. Headline generation