3d Data Science With Python

3D Data Science with Python

Learn to leverage Python for advanced 3D data processing, visualization, and AI-enabled workflows. Define 3D virtual realms, immersive environments, and digital automation to analyze physical objects. With a focus on practicality, this book offers data scientists, engineers, and developers a hands-on approach to working with 3D data. From 3D reconstruction to 3D deep learning techniques, you'll learn how to extract valuable insights from massive datasets, including point clouds, voxels, 3D meshes, images, and more. Author Florent Poux helps you leverage the potential of cutting-edge algorithms and 3D AI models to develop production-ready systems with a focus on automation. You'll learn how to define 3D systems, leverage powerful algorithms, and deploy 3D digital experiences for your industry (geospatial applications, self-driving cars, medical imaging, robotics, manufacturing, computer vision/graphics, and more). This book dives deep into 3D data science with Python: building 3D workflows and wielding Python to implement your solutions. You'll learn: Core concepts and representations of 3D data (meshes, point clouds, voxels, CAD) How to load, manipulate, analyze, and visualize 3D data using powerful Python libraries Advanced AI algorithms for 3D pattern recognition (supervised and unsupervised) 3D reconstruction techniques to generate 3D datasets Automated 3D modeling and generative AI workflows Practical applications of 3D data science in areas like computer vision/graphics, geospatial intelligence, scientific computing, robotics, and autonomous driving How to build end-to-end 3D Python apps through real-world projects Florent Poux is an esteemed authority in the field of 3D data science who teaches and conducts research for top European universities. Heâ s also head professor at the 3D Geodata Academy and innovation director for French Tech 120.

3D Data Science with Python

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 Florent Poux is an esteemed authority in the field of 3D data science who teaches and conducts research for top European universities. He's also head professor at the 3D Geodata Academy and innovation director for French Tech 120 companies.

3D Data Science with Python