Machine Learning with Python

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
2. Logistic Regression
3. k-NN
4. K-MEANS
5. ANN

Prerequisites

Codes run on top of a Docker image, ensuring a consistent and reproducible environment.

You will need to have Docker installed on your machine. You can download it from the Docker website.

To run the code, you will need to first pull the Docker image by running the following command:

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 container

Services can be run by typing the command docker-compose up. This will start the Jupyter Lab on 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.

License

This project is licensed under the MIT License - see the LICENSE file for details.