Coursera Machine Learning by Stanford University
I took Coursera's Machine Learning course by Stanford University around the beginning of the 2021 school year. Andrew Ng teaches supervised and unsupervised machine learning as well as some of the best practices in machine learning. I ended up finishing the first couple of week of this course before to got updated into a specialization. See the github repos for the specialization.
Each topic has its own folder:
- The folder is named (week#).(topic#)-(Description)
- Notes for each sub-section named (section#)-(Description).(txt/md)
- Lecture PDF private
- Quiz with question, answers, and score private
- Octave exercise in a zip file possibly there
- Programming code (in Octave 3.8.0) expanded octave zip file with exercises complete private, possibly
For programming exercises and submissions: There are two programming languages that can be used: Octave or MATLAB. For both some files are given for submissions and exercises described in EnvironmentInstructions.txt. There are also set up instructions for both Octave and MATLAB in 2.1-MultiVarLinearRegression/1-EnvironmentSetup.txt.