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. > - 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.