Engineering reference for Indian students

Machine learning & AI

Natural Language Processing

5 self-contained study topics — notes, diagrams, formulas, and worked examples for exams and GATE.

Topics

Text Preprocessing
For B.Tech exams, text preprocessing is tested for definition plus one direct derivation or numerical; align notation with Goodfellow, Bengio & Courville (Deep Learning).
Word Embeddings
For B.Tech exams, word embeddings is tested for definition plus one direct derivation or numerical; align notation with Tan, Steinbach & Kumar (Introduction to Data Mining).
Sequence Models
For B.Tech exams, sequence models is tested for definition plus one direct derivation or numerical; align notation with Tom Mitchell (Machine Learning).
Attention and Transformers
For B.Tech exams, attention and transformers is tested for definition plus one direct derivation or numerical; align notation with Bishop (Pattern Recognition and Machine Learning).
Evaluation Metrics for NLP
For B.Tech exams, evaluation metrics for nlp is tested for definition plus one direct derivation or numerical; align notation with Goodfellow, Bengio & Courville (Deep Learning).