🌿 a web system to allow users to easily compose and execute full-stack Long Short Term Memory (LSTM) Recurrent Neural Network (RNN) workflows in web browsers by taking advantage of the online spatial data facilities, high-performance computation platforms, and open-source deep learning libraries.
🌿 Aid Learning is a Linux system with GUI running on Android without root. AidLearning is also a Python programming framework for mobile devices. In addition the features available in the Linux environment, AidLearning has supported GUI and neural network environments. For example, Caffe, Tensorflow, Mxnet, ncnn, Keras are perfectly supported.
Active (commit activity)
hwalsuklee/awesome-deep-text-detection-recognition (Reached 500 ⭐)
A curated list of resources for text detection/recognition (optical character recognition ) with deep learning methods.
uber/petastorm (Reached 500 ⭐)
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
abhshkdz/papers (Reached 500 ⭐)
:paperclip: Summaries of papers on deep learning
stratospark/food-101-keras (Reached 500 ⭐)
Food Classification with Deep Learning in Keras / Tensorflow
zzsza/Awesome-Mobility-Machine-Learning-Contents (Reached 50 ⭐)
Machine Learning / Deep Learning Contents in Mobility Industry(Transportation)
deep-geometry/abc-dataset (Reached 50 ⭐)
ABC: A Big CAD Model Dataset For Geometric Deep Learning
microsoft/tensorwatch (Reached 50 ⭐)
Debugging, monitoring and visualization for Deep Learning and Reinforcement Learning
castorini/hedwig (Reached 50 ⭐)
PyTorch deep learning models for document classification
goodrahstar/Python-Deep-Learning-Projects (Reached 50 ⭐)
Codebase for my book "Python DeepLearning Projects" | Learn applied deep learning for various use-cases on NLP, CV and ASR using TensorFlow and Keras. Book link.
alseambusher/Paideia (Reached 50 ⭐)
Know more about your surroundings using Deep Learning