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3D Data Science
This Blueprint shares AI Methods, Algorithms, Tools, Templates and a 6-step System to Build Data Science Solutions for 3D Models: 3D Data Acquisition, Analysis, Modeling, Visualization, and Deployment.
Setting up a 3D data science project involves a combination of data engineering, data analysis, and visualization techniques tailored to handle three-dimensional data.
From gathering initial data to automating 3D immersive experiences, let me cover the entire ladder. I go over all the necessary procedures, resources, and approaches to guarantee an efficient workflow and excellent outcomes.
🦚 Florent’s Note: I wanted to experiment with something a bit more high-level. As a result, you will not have a working implementation of a 3D Transformer Network, but you will gain the understanding to define the next 3D Data Science Venture that you believe has potential.
Let me dive into the 6 main steps: project scope, data acquisition, data pre-processing, data analysis, visualization, and deployment, as illustrated below.
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