Welcome to the "Machine Learning Projects" repository! Here, you will find a collection of machine learning projects that I have worked on. Each project explores different aspects of machine learning, including data analysis, model development, and evaluation.
These projects are primarily developed using the following technologies and platforms:
- Python: The core programming language for all machine learning code.
- Jupyter Notebook: Used for creating interactive and well-documented project notebooks.
- Scikit-Learn: A powerful machine learning library for model development and evaluation.
- Pandas: Used for data manipulation and analysis.
- NumPy: Essential for numerical computations.
- Matplotlib and Seaborn: For data visualization.
- GitHub: The platform where you can find the project repositories and source code.
- Kaggle: To download datasets.
You will find list of machine learning projects available in this repository. Each project directory contains a detailed README with project-specific information.
To get started with any project, you can follow the instructions in the respective project's README. Typically, you will need to:
- Clone the repository to your local machine.
- Install any required dependencies (if not already done).
- Open the project in a Jupyter Notebook or any IDE of your choice.
- Run the code and explore the project.
If you'd like to contribute to any of these projects or have suggestions for improvements, feel free to:
- Fork the repository.
- Create a new branch.
- Make your modifications.
- Submit a pull request.
Your contributions and ideas are always welcome!
This project is licensed under the MIT License - see the LICENSE file for details.
Please don't hesitate to reach out if you have any questions or need further information. Enjoy exploring the world of machine learning!
Created with 🤍 by Madhavi Sonawane.
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