Solutions for Stanford CS229: Machine Learning, Fall 2017

Here are my own solutions to all homeworks, for Prof. Andrew Ng's Masters-Level Machine Learning course

Each problem set's solutions are presented as one or more jupyter notebooks. The top-level jupyter notebooks for each problem set are listed below. They link to other notebooks, for more-involved problems (e.g. Reinforcement Learning in PS#4). Each top-level jupyter notebook includes screenshots of each problem's text and graphics, as a convenience to the reader.

NOTE:

• All errors are my own.
• Because I completed the course materials independently (without access to Teaching Assistants or Recitations), I did consult other CS229 solutions online, to better understand questions, esp. for Locally-Weighted Linear Regression, as well as Reinforcement Learning. Credits:
  • One former student's repo
  • And another's
  • And yet another's (author has since made their repo private)

Problem Set 0: Linear Algebra and Multivariable Calculus

• Problem Set #0
• Answers to Problem Set #0

Problem Set 1: Supervised Learning

• Problem Set #1
• Answers to Problem Set #1

Problem Set 2: Supervised Learning II

• Problem Set #2
• Answers to Problem Set #2

Problem Set 3: Deep Learning & Unsupervised Learning

• Problem Set #3
• Answers to Problem Set #3

Problem Set 4: Expectaion-Maximization, Deep Learning & Reinforcement Learning

• Problem Set #4
• Answers to Problem Set #4