For anyone who wants to dig a bit deeper: PRML by Bishop [0]. An amazing work as a general introduction to machine learning and Bayesian in general. MacKay's book [1] is a bit more opinionated regarding Bayesian methods. Even if you do not become purely Bayesian, it advances your understanding of to approach data quiet a bit compared to the generic "oh data, lets throw a NN at it".

[0] https://www.microsoft.com/en-us/research/people/cmbishop/prm... [1] http://www.inference.org.uk/mackay/itila/book.html