Machine Learning & Data Science

Welcome to the Machine Learning & Data Science repository! This repository contains Jupyter notebooks related to various machine learning and data science libraries such as Pandas, NumPy, Matplotlib, Scikit-learn, and more. These notebooks are designed to help enthusiasts on their ML journey. Additionally, exercise and exercise_solutions notebooks are provided for each library to practice and test your understanding.

Installation

To access the notebooks on your local system, follow these steps:

1. Clone the repository:

   git clone https://github.com/mohsinansari0705/Machine-Learning-Data-Science.git

2. Navigate to the repository directory:

   cd "Machine Learning & Data Science"

3. Create a conda environment (optional but recommended):

   conda create env --perfix [path where you want to create env]

4. Activate the conda environment:

   conda activate [path to your env]

5. Install the required packages:

   conda install pandas, numpy, matplotlib, scikit-learn, jupyter

Usage

Open the Jupyter notebooks using Jupyter Lab or Jupyter Notebook:

jupyter lab
# or
jupyter notebook

Navigate to the desired notebook and start exploring the content. Each notebook is self-contained and includes explanations, code examples, and exercises.

Contributing

We welcome contributions to improve the repository. To contribute, follow these steps:

1. Fork the repository(not forget to star the repo).
2. Create a new branch:

   git checkout -b feature-branch

3. Make your changes and commit them:

   git commit -m "Description of changes"

4. Push to the branch:

   git push origin feature-branch

5. Create a pull request detailing your changes.

License

This repository is licensed under the MIT License. See the LICENSE file for more information.

Happy learning!