Why this JupyterBook?#
Whilst teaching data science courses at EAISI Academy, I often get requests to show how to apply the theory. Given that there is a lot of great content avaialable in the creative commons, I have curated, combined and remixed these into an integrated online curriculum for ease of use.
This foundational data science curriculum is based on the following textbooks and online courses:
Introduction to Statistical Learning with Applications in R, 2nd Edition (ISLRv2) by James, Witten, Hastie, Tibshirani (2021).
Hands-on Machine Learning with Scikit-Learn, Keras and Tensorflow, 2nd Edition (handson-ml2) by Aurélien Géron (2019).
Altair Visualization Curriculum, developed at the University of Washington by Jeffrey Heer, Dominik Moritz, Jake VanderPlas, and Brock Craft.
Interpretable Machine Learning, 2nd Edition (IMLv2) by Christoph Molnar (2022).
Forecasting: Principles and Practice, 3rd Edition (fpp3) by Rob J Hyndman and George Athanasopoulos (2021).
Since three of these use R (ISLRv2, fpp3 and IMLv2), and we have chosen Python as our primary language for instruction, the main contribution of this JupyterBook is to provide a wide set of Python-based notebooks with exercises and examples. Besides my own work, I have integrated various respositories, blog posts etc. which I found useful and fitting within this curriculum. Attributions and links are provided in each section separately.
Getting started with Python for Data Science#
Those new to Python and seeking to get started quickly, I recommend using the following books:
A Whirlwind Tour of Python, by Jake VanderPlas (2016).
Python Data Science Handbook, also by Jake VanderPlas (2018).
Python for Data Analysis, 3rd Edition, by Wes McKinney (2022).
Feedback#
Suggestions, questions and all kinds of feedback are welcome. Please open a new issue using the GitHub button at the top.
Attribution and copyright notice#
© by Daniel Kapitan, Data Science Foundation in Python.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.