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https://www.cs.colostate.edu/~anderson/cs545/
2026-04-05T13:07:07+00:00CS545: Machine Learning
https://www.cs.colostate.edu/~anderson/cs545/
https://www.cs.colostate.edu/~anderson/cs545/lib/tpl/dokuwiki/images/favicon.icotext/html2018-01-20T17:06:47+00:00Anonymous (anonymous@undisclosed.example.com)18sp-schedule
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=18sp-schedule&rev=1516493207&do=diff
text/html2019-12-09T11:44:28+00:00Anonymous (anonymous@undisclosed.example.com)19fa-schedule
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=19fa-schedule&rev=1575917068&do=diff
Schedule
August
Week Topic Material Reading Assignments Week 1:
August 26 - 30 Overview of course and the machine learning field. Reminder of how python is used in machine learning. 01 Introduction to CS545
02 Searching for Good Weights in a Linear Model From Python to Numpy, Chapters 1 - 2
Scipy Lectures, Section 1text/html2019-04-01T20:29:02+00:00Anonymous (anonymous@undisclosed.example.com)19sp-schedule
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=19sp-schedule&rev=1554172142&do=diff
Schedule
Announcements
This is a tentative schedule. Changes will be made as the semester progresses.
January
Week Topic Material Reading Assignments Week 1:
Jan 22 - Jan 25 Overview. Intro to machine learning. Python.text/html2022-06-09T11:48:59+00:00Anonymous (anonymous@undisclosed.example.com)21fa-schedule
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=21fa-schedule&rev=1654796939&do=diff
Schedule
This tentative schedule will be updated during the semester.
August
Week Topic Material Reading Assignments Week 1:
Aug 24, 26 Overview of course. Review of neural networks training and use. 01 Introduction to CS545
02 Searching for Good Weights in a Linear Model Ungradedtext/html2023-04-18T15:19:14+00:00Anonymous (anonymous@undisclosed.example.com)22fa-schedule
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=22fa-schedule&rev=1681852754&do=diff
Please send your suggestions regarding lecture topics to Chuck using this Google Docs form. Questions regarding assignments should be entered in Canvas discussions.
August
Week Topic Material Reading Assignments Week 1:
Aug 23, 256text/html2016-01-11T12:38:22+00:00Anonymous (anonymous@undisclosed.example.com)announcements
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=announcements&rev=1452541102&do=diff
Announcements
Welcome to CS480: Introduction to Machine Learning
Take this course to learn about the very exciting field of machine learning! Companies around the world are using machine learning to analyze all kinds of data. Deep Learning is a machine learning framework that you have, or will, read about in the popular press.text/html2017-05-02T11:41:56+00:00Anonymous (anonymous@undisclosed.example.com)final_project_report
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=final_project_report&rev=1493746916&do=diff
Your Final Project Report
Your final project notebook should include the following sections.
Your report does not have to exactly follow this, and feel free to add
additional material, such as summaries of research articles you found
interesting. Consider this outline as the minimum content for your
reports.text/html2021-07-15T15:44:44+00:00Anonymous (anonymous@undisclosed.example.com)schedule-old
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=schedule-old&rev=1626385484&do=diff
text/html2024-12-07T13:34:24+00:00Anonymous (anonymous@undisclosed.example.com)schedule
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=schedule&rev=1733603664&do=diff
The following schedule is tentative and is being updated.
All students may attend the lecture remotely using this zoom link.
August
Week Topic Lecture Notes Reading Assignments Week 1:
Aug 20, 22 Course overview.text/html2024-08-20T15:00:19+00:00Anonymous (anonymous@undisclosed.example.com)schedule_23_fall
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=schedule_23_fall&rev=1724187619&do=diff
The following schedule is tentative and is being updated.
August
Week Topic Lecture Notes Reading Assignments Week 1:
Aug 20, 22 Course overview. Jupyter notebooks. Animations. 01 Introduction to CS545
02 Searching for Good Weights in a Linear Model JupyterLab Introduction, watch the video then play with jupyter lab.text/html2024-08-20T13:28:18+00:00Anonymous (anonymous@undisclosed.example.com)sidebar
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=sidebar&rev=1724182098&do=diff
* Overview
* Schedule
* Canvas
* Canvas Lecture Recordings
* Canvas Discussions
* Useful_Links
Chuck Anderson
<http://www.colostate.edu>text/html2024-12-07T13:34:24+00:00Anonymous (anonymous@undisclosed.example.com)start
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=start&rev=1733603664&do=diff
The following schedule is tentative and is being updated.
All students may attend the lecture remotely using this zoom link.
August
Week Topic Lecture Notes Reading Assignments Week 1:
Aug 20, 22 Course overview.text/html2024-08-28T11:20:52+00:00Anonymous (anonymous@undisclosed.example.com)syllabus
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=syllabus&rev=1724865652&do=diff
Overview
If you are having trouble registering for the on-campus section, you are welcome to register for the online section.
Description
This course reviews fundamental methods and covers advanced concepts and methods involving deep neural networks for solving problems in data classification, prediction, visualization, and reinforcement learning.text/html2023-10-16T11:31:56+00:00Anonymous (anonymous@undisclosed.example.com)useful_links
https://www.cs.colostate.edu/~anderson/cs545/doku.php?id=useful_links&rev=1697477516&do=diff
Useful Links
This page will contain links to helpful on-line material.
Jobs in Machine Learning
ML jobs, a few near Fort Collins
Negative posts regarding high-tech jobs:
The Hidden Cost of High Salaries in Tech
Why Developers Leave Google
Google is not just firing employees, it is doing something even worse!
Recent News
Distill, useful explanations of machine learning concepts.
ML News Google Group
Connectionists Mailing List
Towards Data Science, introductions and tutorials related …