Generative A.I with PyTorch : A guide to deep learning and artificial intelligence

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(as of Dec 17,2024 22:19:40 UTC – Details)

ASIN ‏ : ‎ B0CS41NJSD
Publication date ‏ : ‎ January 10, 2024
Language ‏ : ‎ English
File size ‏ : ‎ 652 KB
Simultaneous device usage ‏ : ‎ Unlimited
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 186 pages

Generative A.I with PyTorch: A guide to deep learning and artificial intelligence

In recent years, deep learning and artificial intelligence have revolutionized the way we approach complex problems in various fields such as computer vision, natural language processing, and reinforcement learning. One of the most popular frameworks for developing deep learning models is PyTorch, which provides a flexible and dynamic approach to building neural networks.

Generative A.I is a subfield of artificial intelligence that focuses on creating models that can generate new data samples, such as images, text, or music. These models have a wide range of applications, including image synthesis, text generation, and style transfer.

In this guide, we will explore how to use PyTorch to build generative A.I models. We will cover topics such as generative adversarial networks (GANs), variational autoencoders (VAEs), and deep reinforcement learning. We will also provide hands-on examples and code snippets to help you get started with building your own generative A.I models.

By the end of this guide, you will have a solid understanding of how to use PyTorch to create advanced generative A.I models and be well-equipped to explore the exciting possibilities of deep learning and artificial intelligence. Stay tuned for more updates and tutorials on generative A.I with PyTorch!
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