Restricted Boltzmann Machine (RBM)

Restricted Boltzmann Machine is used to detect patterns in data, in an unsupervised way.

If you haven’t read the previous posts yet, you can read them by clicking the below links.

1. Introduction to Machine Learning with TensorFlow »
2. Introduction to Deep Learning »
3. Convolutional Neural Networks »
4. Introduction to Recurrent Neural Networks (RNN) »

Restricted Boltzmann machines (RBMs)

RBMs are self-learning shallow neural networks that learn to reassemble data. They’re significant models because they can extract meaningful features from a given input without having to identify them.

RBMs are useful for unsupervised tasks such as

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