Kdd 2018
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Catboost | 7,564 | 12 | 3 months ago | 20 | September 19, 2023 | 539 | apache-2.0 | Python | ||
| A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU. | ||||||||||
| Person_reid_baseline_pytorch | 3,865 | 3 months ago | 156 | mit | Python | |||||
| :bouncing_ball_person: Pytorch ReID: A tiny, friendly, strong pytorch implement of person re-id / vehicle re-id baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial | ||||||||||
| Dive Into Dl Tensorflow2.0 | 3,588 | a year ago | 22 | apache-2.0 | Jupyter Notebook | |||||
| 本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的认可 | ||||||||||
| Deep Learning Keras Tensorflow | 2,863 | 3 years ago | 12 | mit | Jupyter Notebook | |||||
| Introduction to Deep Neural Networks with Keras and Tensorflow | ||||||||||
| Renderhelp | 1,222 | 3 months ago | 4 | mit | C++ | |||||
| :zap: 可编程渲染管线实现，帮助初学者学习渲染 | ||||||||||
| Oneapi Samples | 758 | 3 months ago | 61 | mit | C++ | |||||
| Samples for Intel® oneAPI Toolkits | ||||||||||
| Deep Learning Wizard | 664 | 6 months ago | 2 | mit | HTML | |||||
| Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, C++ and more. | ||||||||||
| Vulkan_minimal_compute | 538 | 5 years ago | 3 | mit | C++ | |||||
| Minimal Example of Using Vulkan for Compute Operations. Only ~400LOC. | ||||||||||
| Selene | 349 | 6 months ago | 18 | November 22, 2021 | 24 | bsd-3-clause-clear | Jupyter Notebook | |||
| a framework for training sequence-level deep learning networks | ||||||||||
| How To Read Pytorch | 325 | 7 months ago | Jupyter Notebook | |||||||
| Quick, visual, principled introduction to pytorch code through five colab notebooks. | ||||||||||
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