CIS-4320/5320 (Machine Learning) Home Page
This is the home page for Peter Chapin's Machine Learning course notes for the Fall
2022 semester. Here you will find electronic versions of class handouts, homework
assignments, lecture slides, and links to other references of interest. If you are a
student taking Machine Learning consider bookmarking this page.
- The course syllabus gives an overview of the course
and its content, lists course resources, and describes the grading policy and related
- The homework submission area and grade book are on Canvas
5320), but all other course
resources are here.
- The Zoom
meeting URL gives you access to the live lectures and the lab sessions.
- (Optional) You can download and install Python for your platform from the main
Python website. This site has links to a lot of
educational material as well. Installing Python this way is optional because Anaconda
(below) comes with its own Python interpreter.
- We will be using Anaconda and Visual Studio Code to write some programs for this
course. I have prepared some instructions about how to
set up those tools.
- I will distribute sample code via a
Git repository on GitHub. You can use VSCode to clone that repository to your
machine and then use the features of Git to manage your own branches, etc. I will
discuss how to do this in class.
- There are many Python books available in the O'Reilly eBook Collection via the
Hartness Library. Start with Learning Python,
Fifth Edition by Mark Lutz, particular if you are entirely new to Python.
- I've prepared some general information on submitting
- My home page contains other resources of potential
- Here is a checklist of things to do with VSCode to see if
you are able to work with the tool, and with Git, in an effective way. This is not a
graded activity. It is just intended to give your exploration of VSCode a little
Last Revised: 2022-06-27
© Copyright 2022 by Peter C. Chapin <email@example.com>