July 2016
Intermediate to advanced
278 pages
6h 48m
English
Content preview from Advanced Machine Learning with PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Further reading
For a primer on neural networks, it makes sense to read from a range of sources. There are many concerns to be aware of and different authors emphasize on different material. A solid introduction is provided by Kevin Gurney in An Introduction to Neural Networks.
An excellent piece on the intuitions underlying Markov Chain Monte Carlo is available at http://twiecki.github.io/blog/2015/11/10/mcmc-sampling/.
For readers with a specific interest in the intuitions supporting Gibbs Sampling, Philip Resnik, and Eric Hardisty's paper, Gibbs Sampling for the Uninitiated, provides a technical, but clear description of how Gibbs works. It's particularly notable to have some really first-rate analogies! Find them at https://www.umiacs.umd.edu/~resnik/pubs/LAMP-TR-153.pdf ...
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