https://github.com/jtemporal/ml-course-ang-notes
My notes on Andrew Ng's Machine Learning course on Coursera
https://github.com/jtemporal/ml-course-ang-notes
Last synced: 6 days ago
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My notes on Andrew Ng's Machine Learning course on Coursera
- Host: GitHub
- URL: https://github.com/jtemporal/ml-course-ang-notes
- Owner: jtemporal
- License: gpl-3.0
- Created: 2020-01-21T13:47:14.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-01-23T14:58:15.000Z (over 6 years ago)
- Last Synced: 2025-03-02T06:14:28.347Z (over 1 year ago)
- Language: MATLAB
- Size: 104 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Machine Learning by Andrew Ng on Coursera
This are my notes on the course about octave.
For the installation I went to the [GNU Octave website](https://www.gnu.org/software/octave/) and installed the lattest versiont that **isn't** 4.0.0.
I'm currently using Octave 3.8.0 with the experimental GUI downloaded and installed following the course instructions [from here](https://sourceforge.net/projects/octave/files/Octave%20MacOSX%20Binary/2013-12-30%20binary%20installer%20of%20Octave%203.8.0%20for%20OSX%2010.9.1%20%28beta%29/GNU_Octave_3.8.0-6.dmg/download).
All the files have an index at the begin of its name so you can know which one to start your study.
## Repo structure
├── code/ -> Code files directory, all `.m` files are in here
├── images/ -> Images directory, all generated plots are saved as images in here
├── data/ -> Data directory, all generated data and input data are saved as images in here
├── LICENSE -> License for this repo
├── README.md -> Read me file with few useful info
└── notes.md -> study notes that aren't necessarily code