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Mastering PyTorch: From Foundations to Frontiers
Mastering From Foundations to Frontiers is your comprehensive guide to becoming an expert in one of the most powerful machine learning libraries available today. 🔥 This eBook starts with the foundational concepts of PyTorch, including tensors and automatic differentiation. As you progress, you'll delve into building basic neural network architectures and learn how to train your models effectively.
As the chapters advance, the book explores deeper into more complex topics such as convolutional neural networks, recurrent neural networks, and techniques in natural language processing. 🤖 Each section is packed with practical examples and real-world applications, demonstrating how PyTorch can be used to solve challenging problems in various domains like healthcare, autonomous driving, and more.
Mastering From Foundations to Frontiers also covers the latest advancements in PyTorch, including customizing deep learning models and deploying them to production. 🚀 Whether you're a researcher, a software developer, or just a machine learning enthusiast, this eBook equips you with the skills to push the boundaries of what's possible with PyTorch. Unlock the full potential of machine learning with this essential read!
As the chapters advance, the book explores deeper into more complex topics such as convolutional neural networks, recurrent neural networks, and techniques in natural language processing. 🤖 Each section is packed with practical examples and real-world applications, demonstrating how PyTorch can be used to solve challenging problems in various domains like healthcare, autonomous driving, and more.
Mastering From Foundations to Frontiers also covers the latest advancements in PyTorch, including customizing deep learning models and deploying them to production. 🚀 Whether you're a researcher, a software developer, or just a machine learning enthusiast, this eBook equips you with the skills to push the boundaries of what's possible with PyTorch. Unlock the full potential of machine learning with this essential read!
147 pages, Kindle Edition
Published May 12, 2024
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