https://github.com/yetalit/Mojmelo
Machine Learning algorithms in pure Mojo 🔥
https://github.com/yetalit/Mojmelo
Last synced: 21 days ago
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Machine Learning algorithms in pure Mojo 🔥
- Host: GitHub
- URL: https://github.com/yetalit/Mojmelo
- Owner: yetalit
- License: bsd-3-clause
- Created: 2024-08-18T20:40:08.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-10-24T17:26:37.000Z (7 months ago)
- Last Synced: 2024-10-25T07:02:53.452Z (7 months ago)
- Language: Mojo
- Size: 7 MB
- Stars: 13
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-mojo - Mojmelo - Machine Learning algorithms in pure Mojo 🔥 (🗂️ Libraries<a id='libraries'></a> / AI)
README
[![Issues][issues-shield]][issues-url]
[![BSD-3-Clause License][license-shield]][license-url]
## About The Project
The name `Mojmelo` is derived from the "Mojo Machine Learning" expression. It includes the implementation of Machine Learning algorithms from scratch in pure Mojo.
Here is the list of the algorithms:
* Linear Regression
* Polynomial Regression
* Logistic Regression
* KNN
* KMeans
* DBSCAN
* SVM
1. Primal
2. Dual
* Perceptron (single layer: Binary Classification)
* Naive Bayes
1. GaussianNB
2. MultinomialNB
* Decision Tree (both Regression/Classification)
* Random Forest (both Regression/Classification)
* GBDT (both Regression/Classification)
* PCA
* LDA
* Adaboost
Preprocessing:
* normalize
* MinMaxScaler
* StandardScaler
* KFold
* GridSearchCV
**Mojmelo will not only be limited to above algorithms.**
## Getting Started
If you are not familiar with Magic CLI and Mojo projects, here are some links to get you started: (Magic CLI) https://docs.modular.com/magic/ , (Mojo) https://docs.modular.com/mojo/manual/get-started/
### Prerequisites
* Mojo compiler
Additionally, you may want to install bellow Python packages for a better usability and to run tests:
1. Numpy
2. Pandas
3. Scikit-learn
4. Matplotlib
### Installation
There are two ways you can install mojmelo: Using Magic CLI or through the source code.
To complete the installation, you should also finish the setup process which will be discussed later.
#### Magic CLI
Make sure you have the Modular community channel (https://repo.prefix.dev/modular-community) in your `mojoproject.toml` file or `pixi.toml` file in the channels section, then Run the following command:
```
magic add mojmelo
```
To start the setup process, Run the following command from the `main folder` of your project:
```
bash ./.magic/envs/default/etc/conda/test-files/mojmelo/0/tests/setup.sh
```
Note: For better results, please try not to run other tasks on your pc during the setup process.
#### Source Code
You can also install mojmelo through the source code. This way, you will have the source code in your project.
First, Download `mojmelo` folder and `setup.mojo` file. Then Add the following task to your `mojoproject.toml` file or `pixi.toml` file in the tasks section:
```
[tasks]
setup = """
cd &&
mojo ./setup.mojo &&
mojo ./setup.mojo 1 &&
mojo ./setup.mojo 2 &&
mojo ./setup.mojo 3 &&
mojo ./setup.mojo 4 &&
mojo ./setup.mojo 5 &&
mojo ./setup.mojo 6 &&
mojo ./setup.mojo 7 &&
mojo ./setup.mojo 8 &&
mojo ./setup.mojo 9"""
```
Don't forget to change `` according to where `mojmelo` folder and `setup.mojo` file are stored.
Then Run the following command to start the setup process:
```
magic run setup
```
Note: For better results, please try not to run other tasks on your pc during the setup process.
## Usage
Just import any model you want this way:
```python
from mojmelo.LinearRegression import LinearRegression
```
You may also want to use the utility codes I've written for this project:
```python
from mojmelo.utils.Matrix import Matrix
from mojmelo.utils.utils import *
```
## Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.
You can contribute to the project in 3 ways:
1. Apply improvements to the code and Open a Pull Request
2. Report a bug
3. Suggest new features
## Acknowledgments
Took inspiration from Patrick Loeber's MLfromscratch and Erik Linder-Norén's ML-From-Scratch
Mojo usage and distribution is licensed under the [MAX & Mojo Community License](https://www.modular.com/legal/max-mojo-license).
[issues-shield]: https://img.shields.io/github/issues/yetalit/mojmelo
[issues-url]: https://github.com/yetalit/mojmelo/issues
[license-shield]: https://img.shields.io/badge/license-BSD%203--Clause-blue
[license-url]: https://github.com/yetalit/Mojmelo/blob/main/LICENSE
