This repository contains notes and project files related to data science and machine learning using Python. It serves as a resource for understanding various tools and techniques in the field.

The repository is organized into the following directories:

• 1-data-science-and-ml-tools/: Contains notes and examples on essential data science and machine learning tools.

• 2-structured-data-projects/: Includes projects focused on structured data analysis and modeling.

• 3-unstructured-data-projects/: Comprises projects dealing with unstructured data such as text and images.

• data/: Provides datasets used in various projects and examples.

• images/: Contains images and visualizations related to the projects and notes.

To explore the contents of this repository:

1. Clone the repository:

   git clone https://github.com/javedali99/data-science-machine-learning-with-python.git

2. Navigate to the desired directory:

   cd data-science-machine-learning-with-python/1-data-science-and-ml-tools

3. Open the Jupyter notebooks:

   Launch Jupyter Notebook:

   jupyter notebook

   Then, open the notebook of interest to explore the content.

Ensure you have the following installed:

• Python 3.x

• Jupyter Notebook

• Common data science libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn.

Contributions are welcome! If you have suggestions or improvements, feel free to open an issue or submit a pull request.

This project is licensed under the MIT License. See the LICENSE file for details.