Engineering reference for Indian students

Machine learning & AI

Machine Learning

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

Topics

Supervised Learning
For B.Tech exams, supervised learning is tested for definition plus one direct derivation or numerical; align notation with Tom Mitchell (Machine Learning).
Unsupervised Learning
For B.Tech exams, unsupervised learning is tested for definition plus one direct derivation or numerical; align notation with Bishop (Pattern Recognition and Machine Learning).
Model Evaluation Metrics
For B.Tech exams, model evaluation metrics is tested for definition plus one direct derivation or numerical; align notation with Goodfellow, Bengio & Courville (Deep Learning).
Bias Variance Tradeoff
For B.Tech exams, bias variance tradeoff is tested for definition plus one direct derivation or numerical; align notation with Tan, Steinbach & Kumar (Introduction to Data Mining).
Feature Engineering
For B.Tech exams, feature engineering is tested for definition plus one direct derivation or numerical; align notation with Tom Mitchell (Machine Learning).