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Machine Learning Projects

This repository contains a collection of machine learning projects and implementations using various frameworks and datasets. The projects demonstrate techniques ranging from basic algorithms to advanced deep learning models.

Contents

Notebooks and Projects

• TicTacToe:
  Implementation of a simple Tic Tac Toe using Reinforcement Learning.

• fastai_course:
  Projects using the fastai library.

• linear_regression:
  Introduction to linear regression.

• pytorch:
  A directory containing PyTorch projects and examples, cleaned and organized for easy understanding.

• tensorflow:
  Basic image classification task using TensorFlow.

• value_iteration_algorithm:
  Implementation of the value iteration algorithm.

Prerequisites

• Python 3.x
• Libraries required for individual projects are specified in their respective notebooks or scripts.

Setup and Installation

1. Clone the repository:

   git clone https://github.com/mzums/machine-learning.git

2. Navigate to the project directory:

   cd machine-learning

3. Set up the environment by installing the required libraries.

   Example for creating a virtual environment and installing dependencies:

   python -m venv venv
   source venv/bin/activate  # For Unix/Linux
   # or
   venv\Scripts\activate  # For Windows

Usage

Each subdirectory represents a specific project or implementation. Explore the relevant directory for notebooks, datasets, or scripts.

Contribution

Contributions are welcome! To contribute:

1. Fork the repository.
2. Make your changes.
3. Submit a pull request with a detailed description of your changes.

License

This repository is licensed under the MIT License. You are free to use and modify the content.

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Feel free to suggest any improvements or additional features!