Summary

In this final chapter, we moved some distance from our previous discussions of algorithms, configuration and diagnosis to consider tools that improve our experience when implementing deep learning algorithms.

We discovered the advantages to using Lasagne, an interface to Theano designed to accelerate and simplify early prototyping of our models. Meanwhile, we examined TensorFlow, the library developed by Google to aid Deep Learning model adjustment and optimization. TensorFlow offers us a remarkable amount of visibility of model performance, at minimal effort, and makes the task of diagnosing and debugging a complex, deep model structure much less challenging.

Both tools have their own place in our processes, with each being appropriate for a particular set of problems.

Over the course of this book as a whole, we have walked through and reviewed a broad set of advanced machine learning techniques. We went from a position where we understood some fundamental algorithms and concepts,...