This repository provides instructional material for machine learning in python. The material is used for two classes taught at NYU Tandon by Sundeep Rangan:
- EE-UY / CS-UY 4563: Introduction to Machine Learning (Undergraduate)
- EL-GY 9123: Introduction to Machine Learning (Graduate)
Anyone is free to use and copy this material (at their own risk!).
Any feedback
is welcome. The material is very limited now, but lectures and demos will
be added over the course of the class.
Note that lab solutions, homework assignments and lecture notes are given in NYU's proprietary system NYU Classes and are available only to NYU students enrolled in the class. They are not included in the repository.
Both classes assume no python or ML experience. However, experience with some programming language (preferably object-oriented) is required. The class also requires undergraduate probability, linear algebra and multi-variable calculus.
The class progresses in a set of guided demos and labs using the following sequence