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PyTorch deep learning in 7 days

Author: Will Ballard
Publisher: [Place of publication not identified] : Packt, [2019]
Edition/Format:   eVideo : Clipart/images/graphics : English
Summary:
"PyTorch is Facebook’s latest Python-based framework for Deep Learning. It has the ability to create dynamic Neural Networks on CPUs and GPUs, both with a significantly less code compared to other competing frameworks. PyTorch has a unique interface that makes it as easy to learn as NumPy. This 7-day course is for those who are in a hurry to get started with PyTorch. You will be introduced to the most commonly used  Read more...
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Material Type: Clipart/images/graphics, Internet resource, Videorecording
Document Type: Internet Resource, Computer File, Visual material
All Authors / Contributors: Will Ballard
OCLC Number: 1099564418
Notes: Title from title screen (Safari, viewed April 30, 2019).
Release date from resource description page (Safari, viewed April 30, 2019).
Performer(s): Presenter, Will Ballard.
Description: 1 online resource (1 streaming video file (2 hr., 9 min., 36 sec.)) : digital, sound, color
Responsibility: Will Ballard.

Abstract:

"PyTorch is Facebook’s latest Python-based framework for Deep Learning. It has the ability to create dynamic Neural Networks on CPUs and GPUs, both with a significantly less code compared to other competing frameworks. PyTorch has a unique interface that makes it as easy to learn as NumPy. This 7-day course is for those who are in a hurry to get started with PyTorch. You will be introduced to the most commonly used Deep Learning models, techniques, and algorithms through PyTorch code. This course is an attempt to break the myth that Deep Learning is complicated and show you that with the right choice of tools combined with a simple and intuitive explanation of core concepts, Deep Learning is as accessible as any other application development technologies out there. It’s a journey from diving deep into the fundamentals to getting acquainted with the advance concepts such as Transfer Learning, Natural Language Processing and implementation of Generative Adversarial Networks."--Resource description page.

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