A friend recently asked for pointers to learn about machine learning. I’m not an expert, but have spent a bunch of time learning and experimenting, using many different resources. The list below is for people who can already code well enough to build products, but have little/no background in machine learning.
I wrote this list in Fall 2020.
To learn how to do stuff:
- (free online course; excellent pedagogy) [Practical Deep Learning for Coders] (https://course.fast.ai/)
To learn about what’s possible:
- [The Hundred Page Machine Learning Book] (https://www.amazon.com/Hundred-Page-Machine-Learning-Book/dp/199957950X)
To learn from fundamentals - books:
- [Data Science from Scratch (2nd edition)] (https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/1492041130)
- [Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (2nd Edition)] (https://www.amazon.com/gp/product/B07XGF2G87)
To learn from fundamentals - video courses:
- [Machine Learning] (https://www.coursera.org/learn/machine-learning) (this is Andrew Ng’s original machine learning course, and has stood the test of time). NOTE: even though the course says to use Matlab/Octave, you can do all the exercises using python/pandas, using these jupyter notebooks
- [Deep Learning Specialization] (https://www.coursera.org/specializations/deep-learning) (this is newer, and is less theoretical than the one above, with more focus on modern tools)
If you’re not sure where to start, start with Deep Learning for Coders.