Restricted Boltzmann Machines
Offered By: YouTube
Course Description
Overview
Restricted Boltzmann Machines (RBM) are a particular type of Gibbsian network or graphical model that is distinguished by having a layered structure with a hidden and a visible layer and by the fact that units within a layer are not connected to each other, which makes the units statistically independent given the other layer. RBMs can have many units and are often used to model high dimensional data, such as images.
Syllabus
RBM 1.1-1.3 - Restricted Boltzmann Machines (32 min).
RBM 1.4-1.7 - Restricted Boltzmann Machines (25 min).
Taught by
Prof. Laurenz Wiskott
Related Courses
Building Deep Learning Models with TensorFlowIBM via Coursera Deep Learning Fundamentals
Cognitive Class Deep Learning with Tensorflow
IBM via edX Diving Deep into Deep Belief Networks (DBNs)
Pluralsight Deep Learning – Part 2
Indian Institute of Technology Madras via Swayam