Catboost Alternatives
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.
| 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 | a year 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. | ||||||||||
| Rlpyt | 1,709 | 5 years ago | 46 | mit | Python | |||||
| Reinforcement Learning in PyTorch | ||||||||||
| Vkvg | 681 | 2 years ago | 24 | mit | C | |||||
| Vulkan 2D graphics library | ||||||||||
| Awesome Distributed Deep Learning | 309 | 4 years ago | ||||||||
| A curated list of awesome Distributed Deep Learning resources. | ||||||||||
| Finitediff.jl | 221 | a year ago | 17 | other | Julia | |||||
| Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support | ||||||||||
| Mcan Vqa | 181 | 5 years ago | 2 | apache-2.0 | Python | |||||
| Deep Modular Co-Attention Networks for Visual Question Answering | ||||||||||
| Terngrad | 152 | 7 years ago | 6 | apache-2.0 | Python | |||||
| Ternary Gradients to Reduce Communication in Distributed Deep Learning (TensorFlow) | ||||||||||
| Gradient | 85 |  | 7 | 4 years ago | 45 | September 30, 2022 | 7 | other | ||
| This repository serves as a public issue tracker and documentation host for Gradient, full TensorFlow binding for .NET | ||||||||||
| Arboretum | 63 |  | 1 | 5 years ago | 15 | April 04, 2020 | other | Cuda | ||
| Gradient Boosting powered by GPU(NVIDIA CUDA) | ||||||||||
| Cumf_sgd | 62 | 7 years ago | C++ | |||||||
| CUDA Matrix Factorization Library with Stochastic Gradient Descent (SGD) | ||||||||||
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