Welcome! Here the different tutorials for the Machine Learning course are uploaded. We will use Python and Jupyter Notebook. Also, the tutorials use Colaboratory, which is a free Jupyter notebook environment that runs in the cloud.

Each of the notebooks contains this image

which when clicked takes you to the Colaboratory website.

Colaboratory provides cloud computing, so you can modify part of the tutorials and retrain the models to test your modifications.

In this course, we will primarily focus on using the basic Python packages: NumPy, Pandas, Matplotlib, and Seaborn for data analysis and visualisation. These packages provide a solid foundation for data science and analysis tasks. It is important that you become proficient in using these fundamental tools before venturing into more specialised packages.

Please refrain from using additional packages unless explicitly instructed to do so. This will help you build a strong understanding of the core concepts and ensure that you are well-equipped to tackle a wide range of data-related tasks.

To get started with Python and these basic packages, we recommend the following tutorials:

1. Python Programming:

   • Python.org's Official Python Tutorial: A comprehensive guide to Python programming.

2. NumPy:

   • NumPy Quickstart Tutorial: An official guide to getting started with NumPy.

3. Pandas:

   • Pandas Documentation: Official Pandas documentation with tutorials and examples.

4. Matplotlib and Seaborn:

   • Matplotlib Tutorials: Official Matplotlib tutorials and examples.
   • Seaborn Documentation: Official Seaborn tutorial and documentation.

These resources will provide you with a solid foundation in Python and the basic data manipulation and visualisation tools. As the course progresses, we will introduce additional packages as needed.

Sometimes the notebooks do not render correctly in GitHub. You can access directly the notebook in the Colab environment using the following links.

Happy learning!

Best regards,

Abdalrahman M. Abu Ebayyeh