Engineering reference for Indian students

Machine learning & AI

Deep Learning

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

Topics

Neural Network Fundamentals
For B.Tech exams, neural network fundamentals is tested for definition plus one direct derivation or numerical; align notation with Bishop (Pattern Recognition and Machine Learning).
Backpropagation
For B.Tech exams, backpropagation is tested for definition plus one direct derivation or numerical; align notation with Goodfellow, Bengio & Courville (Deep Learning).
Convolutional Neural Networks
For B.Tech exams, convolutional neural networks is tested for definition plus one direct derivation or numerical; align notation with Tan, Steinbach & Kumar (Introduction to Data Mining).
Recurrent Networks and Transformers
For B.Tech exams, recurrent networks and transformers is tested for definition plus one direct derivation or numerical; align notation with Tom Mitchell (Machine Learning).
Regularization Techniques
For B.Tech exams, regularization techniques is tested for definition plus one direct derivation or numerical; align notation with Bishop (Pattern Recognition and Machine Learning).