Classifying handwritten digits
In the previous section, we covered a lot of the theory around NNs, which can be a little bit overwhelming if you are new to this topic. Before we continue with the discussion of the algorithm for learning the weights of the MLP model, backpropagation, let’s take a short break from the theory and see an NN in action.
Additional resources on backpropagation
The NN theory can be quite complex; thus, we want to provide readers with additional resources that cover some of the topics we discuss in this chapter in more detail or from a different perspective:
- Chapter 6, Deep Feedforward Networks, Deep Learning, by I. Goodfellow, Y. Bengio, and A. Courville, MIT Press, 2016 (manuscripts freely accessible at http://www.deeplearningbook.org).
- Pattern Recognition and Machine Learning, by C. M. Bishop, Springer New York, 2006.
- Lecture video slides from Sebastian Raschka’s deep learning course:
