This is the repository, mainly to prepare students to get acquainted with Python, before actually learning machine learning. For those who are more interested in the advanced one, go to my other repository "Machine Learning"
The repo is structured into 2 big components:
Focus on getting started.
- Variables
- List
- Tuples, Dictionaries
- Functions
- Classes
- Exception
- Numpy
- Pandas
- Matplotlib
- Sklearn
- [GERON] Geron, A. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, 2019 (2nd edition) (https://github.com/ageron/handson-ml2)
- [VANDER] VanderPlas, J. Python Data Science Handbook: Essential Tools for Working with Data, 2016 (1st edition) (https://jakevdp.github.io/PythonDataScienceHandbook/)
- Python tutorials available online: https://docs.python.org/3/tutorial/
- Jupyter notebook tutorials available online: https://ipython.org/documentation.html
- Numpy tutorials available online:https://numpy.org/doc/stable/
- Pandas tutorials available online: https://pandas.pydata.org/docs/
- Matplotlib tutorials available online: https://matplotlib.org/contents.html
- Scikit-learn tutorials available online: https://scikit-learn.org/stable/user_guide.html