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Introduction to deep learning : concepts and fundamentals
Title
Introduction to deep learning : concepts and fundamentals / with Laura Graesser.
Publication
[Place of publication not identified] : O'Reilly Media, [2017]
Physical Description
1 online resource (1 streaming video file (55 min., 13 sec.)) : digital, sound, color
Local Notes
Access is available to the Yale community.
Notes
Release information from resource description page (Safari, viewed December 6, 2017).
Title from title screen (Safari, viewed December 6, 2017).
Access and use
Access restricted by licensing agreement.
Summary
"Deep learning neural networks have driven breakthrough results in computer vision, speech processing, machine translation, and reinforcement learning. As a result, neural networks have become an essential part of any data scientist’s toolkit. This course explains what neural networks are, why they are powerful algorithms, and why they have a particular structure. It begins by introducing the core components of a neural network (i.e., nodes, weights, biases, activation functions, and layers). Along the way, you'll learn about the backpropagation algorithm and how neural networks learn. "--Resource description page.
Variant and related titles
O'Reilly Safari. OCLC KB.
Format
Images / Online / Video & Film
Language
English
Added to Catalog
January 15, 2020
Performers
Presenter, Laura Graesser.
Subjects
Genre/Form
Electronic books.
Bookmark As
Citation
