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Florent P. 3D Data Science with Python...Digital Environments with 3D Point 2025
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Category:Other Total size: 51.13 MB Added: 5 months ago (2025-04-11 09:04:01)
Share ratio:7 seeders, 0 leechers Info Hash:07C990E592A0F4C889C85F248727B68E99CAB567 Last updated: 9 hours ago (2025-09-14 01:05:01)
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Description:
Textbook in PDF format
Our physical world is grounded in three dimensions. To create technology that can reason about and interact with it, our data must be 3D too. This practical guide offers data scientists, engineers, and researchers a hands-on approach to working with 3D data using Python. From 3D reconstruction to 3D deep learning techniques, you'll learn how to extract valuable insights from massive datasets, including point clouds, voxels, 3D CAD models, meshes, images, and more.
Dr. Florent Poux helps you leverage the potential of cutting-edge algorithms and spatial AI models to develop production-ready systems with a focus on automation.
You'll get the 3D data science knowledge and code to:
Understand core concepts and representations of 3D data
Load, manipulate, analyze, and visualize 3D data using powerful Python libraries
Apply advanced AI algorithms for 3D pattern recognition (supervised and unsupervised)
Use 3D reconstruction techniques to generate 3D datasets
Implement automated 3D modeling and generative AI workflows
Explore practical applications in areas like computer vision/graphics, geospatial intelligence, scientific computing, robotics, and autonomous driving
Build accurate digital environments that spatial AI solutions can leverage
Who Should Read This Book?
This book is a practical reference for data scientists, engineers, and anyone curious about working with 3D data. It assumes very little, and you’ll find value even without any understanding of Python programming and little familiarity with fundamental data science concepts. Moreover, no prior experience with 3D data processing is necessary. I will guide you through the essential libraries and techniques step by step, ensuring that you can apply the knowledge to real-world scenarios in a 0-to-1 fashion