Restricted Boltzmann Machines
May 1, 2024
5 minute read
Restricted Boltzmann Machines (RBMs) are a type of neural network that is often used in deep learning applications. RBMs are generative models, meaning that they can learn to generate new data that is similar to the data that they were trained on. This makes them useful for tasks such as image generation, text generation, and music generation.
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Reading list
We've selected four books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Restricted Boltzmann Machines.
Provides a comprehensive overview of deep learning, including RBMs. It covers the theory behind deep learning, as well as practical techniques for training and using deep learning models.
Classic introduction to deep learning. It covers a wide range of topics, including RBMs.
Provides a practical introduction to machine learning. It covers a wide range of topics, including RBMs.
Provides a practical introduction to machine learning using Python. It covers a wide range of topics, including RBMs.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/ci72qz/restricted