Dive into Machine Learning

"let's pretend we're working for a startup that just got funded to create a smartphone app that automatically identifies species of flowers from pictures taken on the smartphone. We've been tasked by our head of data science to create a demo machine learning model that takes four measurements from the flowers (sepal length, sepal width, petal length, and petal width) and identifies the species based on those measurements alone."

and write down some questions that come to mind. Also, sign up for Data is Plural, a newsletter of interesting datasets. When a question inspires you, try exploring it with the skills you're learning.

is a popular site to follow, and it can lead you to other resources.

#open-data

has a Discord server and newsletter

Good for people with a strong mathematics background.

An interactive tool to prompt discussions

containers for machine learning.

courses on Deep Learning

by Jeremy Howard and Sylvain Gugger — "an introduction to deep learning, fastai and PyTorch."

is an interesting library that wraps PyTorch, TensorFlow and MXNet models.

Implementations/tutorials of deep learning papers with side-by-side notes. 50+ of them! Really nicely annotated and explained.

It's available in print too!

a machine learning game which asks you questions and guesses an object you are thinking about,

Uses PyMC as well.