Neural Networks A Classroom Approach By Satish Kumar.pdf !free! -

Neural Networks: A Classroom Approach by Satish Kumar (published by Tata McGraw-Hill) is a foundational textbook designed to bridge the gap between biological inspiration and computational implementation in artificial intelligence. Core Overview

• Introduction to deep learning frameworks (TensorFlow, PyTorch, Keras)
• Hands-on sessions: building, training, and testing neural networks
• Real-world applications and case studies

Mathematical Foundations:

Overview of the Book

5.6 Causality, Interpretability & Fairness

• Feature attribution: gradients, Integrated Gradients, SHAP, LIME.
• Saliency maps, attention visualization.
• Fairness: dataset balance, metrics, bias mitigation techniques.

5.3 Self-Supervised Learning

• Contrastive learning (SimCLR, MoCo), masked modeling (BERT), predictive coding.
• Allows representation learning without labels.