Deep Learning
DEEP LEARNING Content:- ### Introduction to Deep Learning 1. **What is Deep Learning?** - Definition and importance - Historical context and evolution - Differences between AI, Machine Learning, and Deep Learning 2. **Applications of Deep Learning** - Computer vision (image classification, object detection, etc.) - Natural language processing (text generation, sentiment analysis, etc.) - Speech recognition - Healthcare (medical imaging, drug discovery, etc.) - Autonomous vehicles - Other real-world applications ### Fundamentals of Neural Networks 3. **Basic Concepts** - Neurons and perceptrons - Activation functions (sigmoid, ReLU, tanh, etc.) - Loss functions (MSE, cross-entropy, etc.) 4. **Training Neural Networks** - Forward and backward propagation - Gradient descent and optimization algorithms (S...