https://github.com/a-mhamdi/mlpy
Machine Learning with Python
https://github.com/a-mhamdi/mlpy
docker-image jupyter-notebook keras-tensorflow machine-learning marimo-notebook python3 sklearn
Last synced: 3 months ago
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Machine Learning with Python
- Host: GitHub
- URL: https://github.com/a-mhamdi/mlpy
- Owner: a-mhamdi
- License: mit
- Created: 2022-09-16T20:51:10.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-04-06T22:51:26.000Z (3 months ago)
- Last Synced: 2025-04-06T23:27:15.205Z (3 months ago)
- Topics: docker-image, jupyter-notebook, keras-tensorflow, machine-learning, marimo-notebook, python3, sklearn
- Language: Jupyter Notebook
- Homepage: https://a-mhamdi.github.io/mlpy/
- Size: 55.9 MB
- Stars: 11
- Watchers: 3
- Forks: 3
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Machine Learning with Python
[](https://github.com/codespaces/new?hide_repo_select=true&ref=main&skip_quickstart=true&machine=standardLinux32gb&repo=537615866&devcontainer_path=.devcontainer%2Fdevcontainer.json&geo=EuropeWest)
[](https://github.com/a-mhamdi/mlpy/actions/workflows/mlpy.yml)
[](https://hub.docker.com/r/abmhamdi/mlpy)This repository contains slides, labs, and code samples for using `Python` to implement some **machine learning** related algorithms.
## Included Algorithms
The repository includes the implementation of the following algorithms:
>1. Linear Regression
>1. Logistic Regression
>1. k-NN
>1. K-MEANS
>1. ANN## Prerequisites
Codes run on top of a `Docker` image, ensuring a consistent and reproducible environment.
> [!IMPORTANT]
>
> You will need to have `Docker` installed on your machine. You can download it from the [Docker website](https://hub.docker.com).> [!NOTE]
> To run the code, you will need to first pull the `Docker` image by running the following command:
>
> ```zsh
> docker pull abmhamdi/mlpy
> ```
>
> This may take a while, as it will download and install all necessary dependencies.## How to control the containers:
* ```docker-compose up -d``` starts the container in detached mode
* ```docker-compose down``` stops and destroys the containerServices can be run by typing the command `docker-compose up`. This will start the `Jupyter Lab` on [http://localhost:2468](http://localhost:2468), and you should be able to use `Python` from within the notebook by starting a new `Python` notebook. You can parallelly start `Marimo` on [http://localhost:1357](http://localhost:1357).
## License
This project is licensed under the MIT License - see the [LICENSE](https://raw.githubusercontent.com/a-mhamdi/mlpy/refs/heads/main/LICENSE) file for details.