Bruno Goncalves - Natural Language Processing (NLP) Fundamentals, 3rd Edition by

Complete
Topics
Complete
1.1 One-hot Encoding
1.2 Bag of Words
1.3 Stop Words
1.4 TF-IDF
1.5 N-grams
1.6 Word Embeddings
1.7 Demo
Topics
2.1 Stemming
2.2 Lemmatization
2.3 Regular Expressions
2.4 Text Cleaning Demo
Topics
3.1 Part of Speech Tagging
3.2 Chunking
3.3 Chinking
3.4 Named Entity Recognition
3.5 Demo
Topics
4.1 Explicit Semantic Analysis
4.2 Document Clustering
4.3 Latent Semantic Analysis
4.4 LDA
4.5 Non-negative Matrix Factorization
4.6 Demo
Topics
5.1 Quantify Words and Feelings
5.2 Negations and Modifiers
5.3 Corpus-based Approaches
5.4 Demo
Topics
6.1 Feed Forward Networks
6.2 Convolutional Neural Networks
6.3 Applications
6.4 Demo
Topics
7.1 Recurrent Neural Networks
7.2 Gated Recurrent Unit
7.3 Long Short-term Memory
7.4 Auto-encoder Models
7.5 Demo
Topics
8.1 Word2vec Embeddings
8.2 GloVe
8.3 Transfer Learning
8.4 Language Detection
8.5 Demo
Topics
9.1 Large Language Models
9.2 Transformers
9.3 BERT
9.4 HuggingFace
9.5 NLP Tasks
9.6 Demo
Natural Language Processing (NLP) Fundamentals: Summary