Artificial Intelligence Deep Learning Machine Learning Tutorials
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
This project is a tool to build CheXNet-like models, written in Keras.
A life simulation for exploring social dynamics
Change Detection Review
A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.
Deep learning driven jazz generation using Keras & Theano!
An implementation of "mixup: Beyond Empirical Risk Minimization"
Keras# initiated as an effort to port the Keras deep learning library to C#, supporting both TensorFlow and CNTK
A multi-channel neural network audio classifier using Keras
A Keras CTC implementation of Baidu's DeepSpeech for model experimentation
A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.
Deep learning operations reinvented (for pytorch, tensorflow, jax and others)
Image Super Resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
Deep Replay - Generate visualizations as in my "Hyper-parameters in Action!" series!
A Deep Learning Amazon Web Service (AWS) AMI that is open, free and works. Run in less than 5 minutes. TensorFlow, Keras, PyTorch, Theano, MXNet, CNTK, Caffe and all dependencies.
Deep-Learning Model Exploration and Development for NLP
a toolkit for pose estimation using deep learning
NLP for human. A fast and easy-to-use natural language processing (NLP) toolkit, satisfying your imagination about NLP.
Algorithm Engineer Toolbox, for the purpose of quickly iterating new ideas
The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud.
整理一些书籍 ,包含 C&C++ 、git 、Java、Keras 、Linux 、NLP 、Python 、Scala 、TensorFlow 、大数据 、推荐系统、数据库、数据挖掘 、机器学习 、深度学习 、算法等。
This repository is the collection of research papers in Deep learning, computer vision and NLP.
PoC code from DEF CON 25 presentation
Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
A Keras implementation of CapsNet in NIPS2017 paper "Dynamic Routing Between Capsules". Now test error ＝ 0.34%.
Siamese LSTM for evaluating semantic similarity between sentences of the Quora Question Pairs Dataset.
BAND：BERT Application aNd Deployment，Simple and efficient BERT model training and deployment, 简单高效的 BERT 模型训练和部署
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network implemented in Keras
Transfer Learning Suite
Transfer Learning Suite in Keras. Perform transfer learning using any built-in Keras image classification model easily!
Artificial intelligence learn playing any game with watching you.
Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.
Tensor Shape Annotation Library (numpy, tensorflow, pytorch, ...)
A playable implementation of Fully Convolutional Networks with Keras.
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
Visualizer for neural network, deep learning, and machine learning models
Screenshot To Code
A neural network that transforms a design mock-up into a static website.
Convert trained PyTorch models to Keras, and the other way around
Yolo Digit Detector
Implemented digit detector in natural scene using resnet50 and Yolo-v2. I used SVHN as the training set, and implemented it using tensorflow and keras.
Neural networks toolbox focused on medical image analysis