Class 15: Introduction to Deep Learning

Summary: Foundation in neural networks and deep learning architectures that power modern AI applications.

Learning Objectives:

• Understand neural network architecture and operations
• Comprehend backpropagation and gradient descent
• Recognize deep learning application domains

Key Topics:

• Neural network fundamentals and perceptrons
• Activation functions and network architectures
• Convolutional Neural Networks (CNN) for image processing
• Recurrent Neural Networks (RNN) for sequential data

Activities

• Neural network architecture design exercise
• Image classification model training
• Deep learning framework exploration