Combines the ease of use of scikit-learn with the power of Theano/Lasagne

nolearn contains a number of wrappers and abstractions around existing neural network libraries, most notably Lasagne, along with a few machine learning utility modules. All code is written to be compatible with scikit-learn. Note nol

Related Repos

pytorch Introduction Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. It provides reference i

philferriere GPU-accelerated Deep Learning on Windows 10 native (Keras/Tensorflow/CNTK/MXNet and PyTorch) >> LAST UPDATED JUNE, 2018 << This latest update: supports 5 frameworks (Keras/Tensorflow/CNTK/MXNet and PyTorch), su

thibo73800 A reinforcement learning environment for self-driving cars in the browser.

rusty1s Documentation | Paper | External Resources PyTorch Geometric (PyG) is a geometric deep learning extension library for PyTorch. It consists of various methods for deep learning on graphs and other irregular structures, also kno

mahyarnajibi SNIPER / AutoFocus: Efficient Multi-Scale Training / Inference SNIPER is an efficient multi-scale training approach for instance-level recognition tasks like object detection and instance-level segmentation. Instead of proces

sjchoi86 ChoiceNet TensorFlow Implementation of ChoiceNet on regression tasks. Summarized result: Classification / Regression Paper: arxiv Classification (MNIST) Result Error type: [Permutation]

NVIDIA NVIDIA DALI Deep learning applications require complex, multi-stage pre-processing data pipelines. Such data pipelines involve compute-intensive operations that are carried out on the CPU. For example, tasks such as: load d

nvidia Introduction This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code here will be included in upstream Pytorch eventually. The intention of Apex is to