> For the complete documentation index, see [llms.txt](https://vikram-bajaj.gitbook.io/cs-gy-6923-machine-learning/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://vikram-bajaj.gitbook.io/cs-gy-6923-machine-learning/master.md).

# Introduction

This book contains my notes for the "Machine Learning" (CS-GY 6923) course that I had taken at NYU Tandon School of Engineering in the Fall of 2018, towards my MS in Computer Science.

The contents of this book have been acquired from several sources, including the presentation slides provided by Prof. Lisa Hellerstein.

Some prerequisites include an understanding of:

* Probability and Statistics
* Simple Differentiation and Integration (especially for polynomials)
* Partial Differentiation
* Chain Rule
* Linear Algebra
* Eigenvectors and Eigenvalues