Machine Learning Labs @ ISETBZ
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This repository contains slides, labs, and code samples for using Python to implement some machine learning related algorithms.
The repository includes the implementation of the following algorithms:
- Linear Regression
- Logistic Regression
- k-NN
- K-MEANS
- ANN
Codes run on top of a Docker image, ensuring a consistent and reproducible environment.
Important
You will need to have
Dockerinstalled on your machine. You can download it from the Docker website.
Note
To run the code, you will need to first pull the `Docker` image by running the following command:docker pull abmhamdi/mlpyThis may take a while, as it will download and install all necessary dependencies.
docker compose up -d starts the container in detached modedocker compose down stops and removes the containerServices 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.
This project is licensed under the MIT License - see the LICENSE file for details.
Content type
Image
Digest
sha256:1c0ede1d9…
Size
618.7 MB
Last updated
10 months ago
docker pull abmhamdi/mlpy