O'Reilly logo

Hands-On Machine Learning with C# by Matt R. Cole

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Restricted Boltzmann Machines

One popular method of constructing a Deep Belief Network is to comprise it as a layered collection of Restricted Boltzmann Machines (RBMs). These RMBs function as auto-encoders, with each hidden layer, serving as the visible layer for the next. This composition leads to a fast, layer-by-layer and unsupervised training procedure. The Deep Belief Network will have layers of RBMs for the pre-train phase, and then a feedforward network for the fine-tune phase. The first step of the training will be to learn a layer of features from the visible units. The next step is to take the activations from the previously trained features and make them the new visible units. We then repeat the process so that we can learn more ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required