Restricted Boltzmann Machine: Fundamentals and Applications for Unlocking the Hidden Layers of Artificial Intelligence

A restricted Boltzmann machine, often known as an RBM, is an example of an artificial neural network that is stochastic and generative and has the ability to develop a probability distribution over its own set of inputs.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Restricted Boltzmann Machine

Chapter 2: Boltzmann Distribution

Chapter 3: Entropy (Information Theory)

Chapter 4: Unsupervised Learning

Chapter 5: Mutual Information

Chapter 6: Boltzmann Machine

Chapter 7: Cross Entropy

Chapter 8: Softmax Function

Chapter 9: Autoencoder

Chapter 10: Deep Belief Network

(II) Answering the public top questions about restricted boltzmann machine.

(III) Real world examples for the usage of restricted boltzmann machine in many fields.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of restricted boltzmann machine.

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