Sometimes I get asked how to learn computional methods, and there is quite a lot of great, free reading material and tools to get you started (or go further).

Great Free Textbooks

These first two are probably the best books on Machine Learning that I have read. I highly recomend them both

Deep Learning (Ian Goodfellow and Yoshua Bengio and Aaron Courville):

Information Theory, Inference, and Learning Algorithms (David Macay)

This books is also fantastic

Pattern Recognition and Machine Learing (Christopher Bishop)

Non-Free (but still really good) TextBooks

Bayesain Data Analysis, for beginners

Doing Bayesian Data Analysis (John Kruschke)

Bayesain Data Analysis, for the more mathematically inclined

Bayesian Data Analysis (Andrew Gelman, et al)

Computational Tools

Neural networks

I use Keras typically. I would recomend this as it has a lot of very reasonable defaults for most uses. Pytorch is also very good but for those who want more control.

Bayesian Inference

I use pymc3 personally, which is python based.

Stan is computationally equivalent, but more compatable with r.