Links
Always growing list of cool, free learning/fun/useful resources out there that will make you love the internet.
Tutorials
- calmcode: A goldmine – learn calmly bit by bit with hands-on tutorials.
- Real Python: Awesome in depth tutorials about all sorts of aspects of the language.
- Scipy Lectures: Learn numerics, scientific and data oriented Python.
- Numba - Tell Those C++ Bullies to Get Lost - Forsyth & Barba - SciPy 2017
- Reproducible workflow in Jupyter - Jake van der Plas
- Anatomy of Matplotlib - Root & Aizenman - SciPy 2018
- Docker: Nail down the basics with this tutorial from freeCodeCamp.
- SQL: Interactive book, aims to be “the best place on the internet for learning SQL” - you decide.
- Git: Go beyond typing commands blindly - understand git’s data model.
- Git-Advanced: Be more productive with these few more advanced concepts, e.g., rebase, cherry-picking, etc.
- fast.ai: A myriad of learning resources – ML, python, developer tools, etc.
- Setosa: visual explanations
- Transformers & Attention: A great explanation by V. Warmerdam at Rasa Whiteboard series.
- The math behind Attention: Keys, Queries, and Values matrices: Geometric intuitions behind attention mechanism, a beautiful piece by L. Serrano.
- Load balancing with great visuals
Talks
- Choose Boring Technology – Dan McKinley
- Facts and Myths about Python names and values - Ned Batchelder - PyCon 2015
- Statistics for Hackers - Jake van der Plas - PyCon 2016
- Built in Super Heroes - David Beazley - PyData 2016
- Computational Statistics - Allen Downey - SciPy 2017
- A Bluffer’s Guide to Dimension Reduction - Leland McInnes - PyData 2018
- Untitled12 - Vincent Warmerdam - PyData 2019
- Gaussian Progress – Vincent Warmerdam - PyData 2019
Youtube channels
- 3brown1blue: One of the best teachers in the internet. Ever.
- Corey Schafer: Hands down one of the best Python resources out there.
- anthonywritescode: Mostly (not only) Python features, tools & idioms explained.
- Real Python
- Luis serrano: Machine learning algorithms and intuitions, in simple words.
- Luke Smith: Unix, vim, latex, markdown, free-software, etc.
- Python Engineer
- Ben Lambert: Stats, ML, Bayesian stuff.
- Statsquest – Josh Starmer: Stats, machine learning, algorithms, bam!
- Arxiv Insights: Machine learning papers explained and discussed.
Blogs
- Vincent Warmerdam: Data, machine learning, algorithms – and nice drawings.
- Max Halford
- Adam Johnson: Mostly Python, tackling core aspects of the language.
- Squirrel, Not Squirrel: Amazing PCA explanation.
- Michael Nielsen
- MLU-EXPLAIN: Visual explanations of core machine learning concepts.
Podcasts
Python & co.
Data, ML, Maths, etc.
- Vanishing Gradients - Hugo Bowne-Anderson
- The Gradient Podcast
- The Robot Brains Podcast - Peter Abeel
- Practical AI
- AI in action
- Machine Learning Street Talks
- Complexity - Sta. Fe Institute
- This week in machine learning
- Underrated ML
- Talking Machines
- Numberphile
- Data skeptic
- Linear Digressions
- Gradient dissent: Weights and biases
- Dataframed
- Partially derivative