Lab1 : Perceptron Implementation
Chapter 1: Recall of ML Basics - Perceptron
Chapter 2: MLP Architecture, Inference, Backprop.
Chapter 3: Activation Functions - Regularization
Chapter 4: Convolutional Neural Networks
Lab 2: Perceptron Implementation from Scratch - Classification
Lab 3: Hands-on TensorFlow: Tensors and Automatic Differentiation
Lab 4: Handwritten Digit Recognition
Lab 5: Underfitting and Overfitting - Regularization
Lab 6: Midterm Preparation
Lab 7: Convolutional Neural Networks