Kód: 41945977
Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with easeKey Features:Understand 3D data processing with rendering, PyTorch optimizatio ... celý popis
Angličtina
Nákupem získáte 99 bodů
Anotace knihy
Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with ease
Key Features:
Book Description:
With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time.
Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library.
By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently.
What You Will Learn:
Who this book is for:
This book is for beginner to intermediate-level machine learning practitioners, data scientists, ML engineers, and DL engineers who are looking to become well-versed with computer vision techniques using 3D data.
Parametry knihy
Zařazení knihy Knihy v němčině Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Informatik, EDV - Sonstiges
991 Kč
Angličtina
Osobní odběr Praha, Brno a 47410 dalších
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