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Introduction to deep learning using PyTorch : create simple neural networks in Python using PyTorch / with Goku Mohandas & Alfredo Canziani.

By:

Mohandas, Goku [on-screen presenter.]

Contributor(s):

Publisher: [Place of publication not identified] : O'Reilly, [2018]Description: 1 online resource (1 streaming video file (1 hr., 27 min.)) : digital, sound, colorContent type:

two-dimensional moving image

Media type:

computer
video

Carrier type:

online resource

Subject(s):

Genre/Form:

Electronic books.

Online resources:

Click here to access online

Presenters, Goku Mohandas, Alfredo Canziani.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. Finally, we will CUDA render our code in order to be GPU-compatible for even faster model training."--Resource description page.

Item type:

eBooks

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Includes bibliographical references and index.

Title from title screen (Safari, viewed February 22, 2018).

Release date from resource description page (Safari, viewed February 22, 2018).

Presenters, Goku Mohandas, Alfredo Canziani.

"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.