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Is anyone able to recommend some resources (preferably books) on the topic of neural networks that goes beyond that of introductory reading?

I'm still relatively new to the subject, however I have successfully created my own Neural Network so I wouldn't consider myself a beginner, so I'm looking for something more intermediate.

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http://machinelearningmastery.com. Books from Jason are really good. Focusing on practical applications rather than theory.

One more awesome resource is Stanford's csc231n lectures. That's the best course you can take to know about Neural Networks. It has indepth details on theory including how to create your own backprop algorithms etc and practical stuffs like tips and tricks to get best results. The course covers all aspects of NNs especially CNNs.

Hope this helps

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I would suggest following free resources

  1. Neural Networks and Deep Learning by Michael Nielsen is good for beginners.
  2. Deep Learning book by Ian Goodfellow and Yoshua Bengio and Aaron Courville covers basic math required for ANNs.
  3. Udacity Deep Learning course is very hands on, you learn to code in Tensorflow.
  4. Geoffrey Hinton's Neural Network course on Coursera covers theoretical background for ANNs.
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Neural Network Design 2ed by Hagan is one resource you could look at. It's a huge tome, weighing in at over 1000 pages in pdf form, but it is freely available (you can also buy a dead-tree version if you really want one).

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I would recommend Machine Learning by Tom M.Mitchell,which provides key algorithms and theory that forms the core of machine learning

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  • $\begingroup$ I would kind request you to add some details to your answer and also try to check this out Artificial Intelligence $\endgroup$ – quintumnia Jul 15 '17 at 17:50

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