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
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