Pytorch Artificial Intelligence Fundamentals


Download Pytorch Artificial Intelligence Fundamentals PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Pytorch Artificial Intelligence Fundamentals book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.

Download

PyTorch Artificial Intelligence Fundamentals


PyTorch Artificial Intelligence Fundamentals

Author: Jibin Mathew

language: en

Publisher:

Release Date: 2020-02-28


DOWNLOAD





Artificial Intelligence Fundamentals (ASQ's Pocket Guide)


Artificial Intelligence Fundamentals (ASQ's Pocket Guide)

Author: Jayet Moon

language: en

Publisher: Quality Press

Release Date: 2025-04-15


DOWNLOAD





How is understanding artificial intelligence (AI) and machine learning (ML) useful to a quality professional? The answer may surprise you. With Artificial Intelligence Fundamentals, you’ll learn how these new technologies can be integrated into everyday quality management practices to make your work faster, efficient, scalable, and more effective. Author Jayet Moon covers a wide range of topics, including working with ChatGPT, successfully using AI for problem solving, and following best practices.

PyTorch Essentials: A Comprehensive Guide to Machine Learning Techniques


PyTorch Essentials: A Comprehensive Guide to Machine Learning Techniques

Author: Adam Jones

language: en

Publisher: Walzone Press

Release Date: 2024-12-03


DOWNLOAD





"PyTorch Essentials: A Comprehensive Guide to Machine Learning Techniques" is an essential resource for programmers, researchers, and enthusiasts eager to enhance their mastery of machine learning and artificial intelligence through the PyTorch framework. This guide deftly combines theoretical foundations with hands-on applications, covering everything from basic tensor manipulation and neural network creation to sophisticated architectures such as CNNs, RNNs, and generative models. Additionally, it delves into reinforcement learning, optimization strategies, and best practices for deployment, empowering readers with the skills to develop scalable, production-ready solutions. Whether advancing your research or solving real-world industry challenges, this book serves as your indispensable guide to mastering machine learning with PyTorch.