Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

A curated list of resources for Learning with Noisy Labels

A Web app that supports mentorship programs at Visionary Education Foundation (远见教育基金会).

Aqueduct is no longer being maintained. Aqueduct allows you to run LLM and ML workloads on any cloud infrastructure.

study resources of model and engineering

Object detection, 3D detection, and pose estimation using center point detection:

A cheatsheet of modern C++ language and library features.

In-depth tutorials for implementing deep learning models on your own with PyTorch.

A paper list of lane detection.

This is the code for the NeurIPS 2019 paper Region Mutual Information Loss for Semantic Segmentation.

A collection of loss functions for medical image segmentation

nanoflann: a C++11 header-only library for Nearest Neighbor (NN) search with KD-trees

🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.

A lean C++ library for working with point cloud data

C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud

A list of papers and datasets about point cloud analysis (processing)

implementation "Escape from Cells: Deep Kd-Networks for The Recognition of 3D Point Cloud Models" in pytorch

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

Converts profiling output to a dot graph.