Welcome to the Machine Learning Models Repository! This repository contains implementations of various machine learning models, including linear regression, SVM, neural network, logistic regression, and a Naive Bayes classifier. Additionally, it includes a project that utilizes all these models.
- Implementation of the linear regression model using Python and NumPy.
- Implementation of the SVM model using both a machine learning library (e.g., scikit-learn) and from scratch using Python and NumPy.
- Implementation of a basic neural network from scratch using Python and NumPy.
- Implementation of logistic regression from scratch using Python and NumPy.
- Implementation of a Naive Bayes classifier using Python.
The project included in this repository demonstrates the application of the above machine learning models in a real-world scenario. It showcases how these models can be integrated and utilized together to solve a specific problem or task. Details about the project can be found in the project directory. Explore individual model implementations in their respective directories.
. Explore the project directory to understand how the models are integrated and utilized together.
Contributions to this repository are welcome! If you have suggestions for improvements, bug fixes, or additional models to implement, feel free to open an issue or submit a pull request.
This repository is licensed under the MIT License, which means you are free to use, modify, and distribute the code for both commercial and non-commercial purposes. However, please attribute the original authors and include a copy of the license in your derivative works.
If you have any questions, comments, or feedback regarding this repository, feel free to reach out to the maintainers:
s.abd@zewailcity.edu.eg We hope you find this repository useful for learning and exploring machine learning models!