Reading List
Updated Started
Sources used in these notes
- Dan Becker, Machine Learning for Business Decision Optimization: the decision optimisation notes.
- Richard McElreath, Statistical Rethinking: the Bayesian data analysis note.
- Joel Grus, Data Science from Scratch: much of the statistics notes and the gradient descent note.
- Kaggle, Geospatial Analysis: the geospatial notes.
- Christoph Molnar, Interpretable Machine Learning: background for the interpretability notes.
To read
- Jason Brownlee, Imbalanced Classification with Python
- Lewis Tunstall, Leandro von Werra and Thomas Wolf, Natural Language Processing with Transformers
Useful tools
- GeoGebra for plotting functions and geometry
- Wolfram Alpha for checking algebra and calculus
Revision log
- Moved from the data-science-notes index page
Tags: Data Science