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Introduction to deep learning using PyTorch : create simple neural networks in Python using PyTorch

Author: Goku Mohandas; Alfredo Canziani
Publisher: [Place of publication not identified] : O'Reilly, [2018]
Edition/Format:   eVideo : Clipart/images/graphics : English
Summary:
"This video will serve as an introduction to PyTorch, a dynamic, deep learning framework in Python. In this video, you will learn to create simple neural networks, which are the backbone of artificial intelligence. We will start with fundamental concepts of deep learning (including feed forward networks, back-propagation, loss functions, etc.) and then dive into using PyTorch tensors to easily create our networks.  Read more...
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Details

Material Type: Clipart/images/graphics, Internet resource, Videorecording
Document Type: Internet Resource, Computer File, Visual material
All Authors / Contributors: Goku Mohandas; Alfredo Canziani
OCLC Number: 1023864125
Notes: Title from title screen (Safari, viewed February 22, 2018).
Release date from resource description page (Safari, viewed February 22, 2018).
Performer(s): Presenters, Goku Mohandas, Alfredo Canziani.
Description: 1 online resource (1 streaming video file (1 hr., 27 min.)) : digital, sound, color
Responsibility: with Goku Mohandas & Alfredo Canziani.

Abstract:

"This video will serve as an introduction to PyTorch, a dynamic, deep learning framework in Python. In this video, you will learn to create simple neural networks, which are the backbone of artificial intelligence. We will start with fundamental concepts of deep learning (including feed forward networks, back-propagation, loss functions, etc.) and then dive into using PyTorch tensors to easily create our networks. Finally, we will CUDA render our code in order to be GPU-compatible for even faster model training."--Resource description page.

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