Summer ML

This is the course website for NYU Tandon's 2020 Summer Program for Machine Learning. Materials are adapted from last year's course by Nikola Janjusevic, Akshaj Kumar Veldanda, Jacky Yuan, Tejaishwarya Gagadam.

Logistics:

• We use Piazza for offline discussion!

Topic Schedule:

Day 1: Introduction to ML

• Lecture Notes
• Annotated Lecture Notes
• Demo: Python Basics with Solutions

Day 2: Python Basics

• Lecture Notes
• Annotated Lecture Notes
• Demo: Numpy Vectors and Matrices
• Demo: Matplotlib Plotting
• Lab: Visualizing Icebreaker Dataset
• Demo: Boston Housing Dataset: Single Variable

Day 3: Linear Regression

• Lecture Notes
• Annotated Lecture Notes
• Demo: Boston Housing Dataset: Single Variable
• Demo: Boston Housing Dataset: Multilinear Regression

Day 4: Overfitting and Generalization

• Lecture Notes
• Annotated Lecture Notes
• Demo: Polynomial Fitting
• Demo: Overfitting and Regularization
• Demo: Gradient Descent

Day 5: Linear Classification and Mini Project

• Lecture Notes
• Annotated Lecture Notes
• Project: Fish Weight Prediction
• Alternative Solutions to the Project

Day 6: Neural Networks

• Lecture Notes
• Annotated Lecture Notes
• Demo: Iris

Day 7: PyTorch Basics

• Readings: Course Notes from Stanford CS231n
• Demo: Pytorch Basics
• Lab: Solve the Mini-Project with MLPs

Day 8: Convolutional Neural Networks

• Lecture Notes
• Annotated Lecture Notes
• Demo: Fashion MNIST
• Lab: Cats vs. Dogs

Day 9: Final Project

• Lecture Notes
• Project: CIFAR10 Classification
• Project: Car Classification

Day 10: Deep Learning Applications and its Social Impact

• Lecture Notes
• Demo: Generative Adversarial Networks