Tutorials for pointcloud processing in Python (transformations, spatial indexing, subsampling, cleaning, normals & curvatures, descriptors, segmentation, primitive fitting, registration, ...

Distributed training is a model training paradigm that involves spreading training workload across multiple worker nodes, therefore significantly improving the speed of training and model accuracy.