🌿 Nyoka is a Python library for comprehensive support of the latest PMML (PMML 4.4) standard. Using Nyoka, Data Scientists can export a large number of Machine Learning and Deep Learning models from popular Python frameworks into PMML by either using any of the numerous included ready-to-use exporters or by creating their own exporter for specialized/individual model types by simply calling a sequence of constructors.
Active (commit activity)
iperov/DeepFaceLab (Reached 5000 ⭐)
DeepFaceLab is a tool that utilizes machine learning to replace faces in videos. Includes prebuilt ready to work standalone Windows 7,8,10 binary (look readme.md).
udacity/deep-learning-v2-pytorch (Reached 2000 ⭐)
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
NVIDIA/DeepLearningExamples (Reached 1000 ⭐)
Deep Learning Examples
aidlearning/AidLearning-FrameWork (Reached 500 ⭐)
AidLearning build a Linux OS running on the Android with GUI, Deep-Learning and Python Visual Programming support . Caffe, Tensorflow, mxnet, Keras,Pytorch are perfectly supported.Python+linux+Android+AI 4in1 environments.
singaxiong/SignalGraph (Reached 100 ⭐)
Matlab-based deep learning toolkit that supports arbitrary directed acyclic graphs (DAG). Support DNN, LSTM, CNN layers and many signal processing layers. Include recipes/examples of using the tool for various tasks.
Cadene/block.bootstrap.pytorch (Reached 100 ⭐)
BLOCK (AAAI 2019), with a multimodal fusion library for deep learning models
stared/thinking-in-tensors-writing-in-pytorch (Reached 50 ⭐)
Thinking in tensors, writing in PyTorch (a hands-on deep learning intro)
L706077/DNN-Dialogue-System-Papers (Reached 50 ⭐)
awesome deep learning papers for dialog systems
nerox8664/awesome-computer-vision-models (Reached 50 ⭐)
It's the list with popular deep learning models related to classification and segmentation task
embedeep/Free-TPU (Reached 50 ⭐)
Free TPU for FPGA with Lenet, MobileNet, Squeezenet, Resnet, Inception V3, YOLO V3, and ICNet. Deep learning acceleration using Xilinx zynq (Zedboard or ZC702 ) or kintex-7 to solve image classification, detection, and segmentation problem.