https://github.com/devalone/machine-learning-course-by-andrew-ng-in-rust

Implementation of algorithms from machine learning course by Andrew Ng https://www.coursera.org/learn/machine-learning/
https://github.com/devalone/machine-learning-course-by-andrew-ng-in-rust

andrew-ng-course andrew-ng-coursera andrew-ng-machine-learning andrew-ng-ml-course linear-regression logistic-regression machine-learning neural-networks rust

Last synced: 3 months ago
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Implementation of algorithms from machine learning course by Andrew Ng https://www.coursera.org/learn/machine-learning/

• Host: GitHub
• URL: https://github.com/devalone/machine-learning-course-by-andrew-ng-in-rust
• Owner: DevAlone
• Created: 2021-03-25T20:03:00.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2022-02-09T21:17:28.000Z (over 3 years ago)
• Last Synced: 2025-01-14T14:26:52.161Z (5 months ago)
• Topics: andrew-ng-course, andrew-ng-coursera, andrew-ng-machine-learning, andrew-ng-ml-course, linear-regression, logistic-regression, machine-learning, neural-networks, rust
• Language: Rust
• Homepage:
• Size: 15.4 MB
• Stars: 1
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# machine-learning-course-by-andrew-ng-in-rust

## Week 1

`week1` dir contains linear regression demo for the first week.

Just run it, click to create additional points and see how it converges.

![a screenshot of the UI](https://github.com/DevAlone/machine-learning-course-by-andrew-ng-in-rust/blob/master/assets/week1/1.300x.png?raw=true)

![a video of the UI](https://github.com/DevAlone/machine-learning-course-by-andrew-ng-in-rust/blob/master/assets/week1/2.gif?raw=true)

## Week 2

`week2` dir contains linear regression with multiple features demo for the second week. The implementation works with

any number of features, but we use 2 because human beings have troubles perceiving more than 3 dimensions.

You can left click the image and rotate it with the mouse and add points by the inputs on the bottom.

There 2 algorithms: linear regression and normal equation and you can switch between them by

changing `USE_NORMAL_EQUATION` in `src/constants.rs` file

![a screenshot of the UI](https://github.com/DevAlone/machine-learning-course-by-andrew-ng-in-rust/blob/master/assets/week2/1.300x.png?raw=true)

![a screenshot of the UI](https://github.com/DevAlone/machine-learning-course-by-andrew-ng-in-rust/blob/master/assets/week2/2.300x.png?raw=true)

![a video of the UI](https://github.com/DevAlone/machine-learning-course-by-andrew-ng-in-rust/blob/master/assets/week2/3.gif?raw=true)

## Week 3

`week3` dir contains a demo for logistic regression with 1 and 2 features. For 2 features there's a 2d visualization

where x, y and size of the dot are original data. For 3 features we visualize points in 3d space and prediction function

as a sigmoid surface. You can add new points and see how the surface will get adjusted.

![a screenshot of the UI](https://github.com/DevAlone/machine-learning-course-by-andrew-ng-in-rust/blob/master/assets/week3/1.300x.png?raw=true)

![a screenshot of the UI](https://github.com/DevAlone/machine-learning-course-by-andrew-ng-in-rust/blob/master/assets/week3/2.300x.png?raw=true)

![a video of the UI](https://github.com/DevAlone/machine-learning-course-by-andrew-ng-in-rust/blob/master/assets/week3/3.gif?raw=true)

![a video of the UI](https://github.com/DevAlone/machine-learning-course-by-andrew-ng-in-rust/blob/master/assets/week3/4.gif?raw=true)

## Week 4

There's no demo for week 4 since week 5's demo includes the material from week 4.