|
28 | 28 | - [Deep Learning](#deep-learning) |
29 | 29 | - [PyTorch](#pytorch) |
30 | 30 | - [TensorFlow](#tensorflow) |
31 | | - - [MXNet](#mxnet) |
32 | 31 | - [JAX](#jax) |
33 | 32 | - [Others](#others) |
34 | 33 | - [Automated Machine Learning](#automated-machine-learning) |
|
156 | 155 | * [Elephas](https://github.com/maxpumperla/elephas) - Distributed Deep learning with Keras & Spark. <img height="20" src="img/keras_big.png" alt="Keras compatible"> |
157 | 156 | * [qkeras](https://github.com/google/qkeras) - A quantization deep learning library. <img height="20" src="img/keras_big.png" alt="Keras compatible"> |
158 | 157 |
|
159 | | -### MXNet |
160 | | -* [MXNet](https://github.com/apache/incubator-mxnet) - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler. <img height="20" src="img/mxnet_big.png" alt="MXNet based"> |
161 | | -* [Gluon](https://github.com/gluon-api/gluon-api) - A clear, concise, simple yet powerful and efficient API for deep learning (now included in MXNet). <img height="20" src="img/mxnet_big.png" alt="MXNet based"> |
162 | | -* [Xfer](https://github.com/amzn/xfer) - Transfer Learning library for Deep Neural Networks. <img height="20" src="img/mxnet_big.png" alt="MXNet based"> |
163 | | -* [MXNet](https://github.com/ROCmSoftwarePlatform/mxnet) - HIP Port of MXNet. <img height="20" src="img/mxnet_big.png" alt="MXNet based"> <img height="20" src="img/amd_big.png" alt="Possible to run on AMD GPU"> |
164 | | - |
165 | 158 | ### JAX |
166 | 159 | * [JAX](https://github.com/google/jax) - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more. |
167 | 160 | * [FLAX](https://github.com/google/flax) - A neural network library for JAX that is designed for flexibility. |
|
184 | 177 |
|
185 | 178 | ## Natural Language Processing |
186 | 179 | * [torchtext](https://github.com/pytorch/text) - Data loaders and abstractions for text and NLP. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible"> |
187 | | -* [gluon-nlp](https://github.com/dmlc/gluon-nlp) - NLP made easy. <img height="20" src="img/mxnet_big.png" alt="MXNet based"> |
188 | 180 | * [KerasNLP](https://github.com/keras-team/keras-nlp) - Modular Natural Language Processing workflows with Keras. <img height="20" src="img/keras_big.png" alt="Keras based/compatible"> |
189 | 181 | * [spaCy](https://spacy.io/) - Industrial-Strength Natural Language Processing. |
190 | 182 | * [NLTK](https://github.com/nltk/nltk) - Modules, data sets, and tutorials supporting research and development in Natural Language Processing. |
|
209 | 201 | ## Computer Vision |
210 | 202 | * [torchvision](https://github.com/pytorch/vision) - Datasets, Transforms, and Models specific to Computer Vision. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible"> |
211 | 203 | * [PyTorch3D](https://github.com/facebookresearch/pytorch3d) - PyTorch3D is FAIR's library of reusable components for deep learning with 3D data. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible"> |
212 | | -* [gluon-cv](https://github.com/dmlc/gluon-cv) - Provides implementations of the state-of-the-art deep learning models in computer vision. <img height="20" src="img/mxnet_big.png" alt="MXNet based"> |
213 | 204 | * [KerasCV](https://github.com/keras-team/keras-cv) - Industry-strength Computer Vision workflows with Keras. <img height="20" src="img/keras_big.png" alt="MXNet based"> |
214 | 205 | * [OpenCV](https://github.com/opencv/opencv) - Open Source Computer Vision Library. |
215 | 206 | * [Decord](https://github.com/dmlc/decord) - An efficient video loader for deep learning with smart shuffling that's super easy to digest. |
|
0 commit comments