Topic: recurrent-neural-networks

PyTorch Tutorial for Deep Learning Researchers

Neural networks in JavaScript

:computer: Make machines learn so that you don't have to program them; The ultimate list

An implementation of "Tracking the World State with Recurrent Entity Networks".

Human activity recognition using TensorFlow on smartphones dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

Spying using Smartwatch and Deep Learning

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling. It's written by C# language and based on .NET framework 4.6 or above version. RNNSharp supports many different types

:art: Buttery Smooth Automatic Differentiation in C++

DNC-theano : A theano implementation of DeepMind's DNC model

Tensorflow implementation of the HarvardNLP paper - What You Get Is What You See: A Visual Markup Decompiler (https://arxiv.org/pdf/1609.04938v1.pdf)

[Deprecated] Source Code Generation using Sequence Generative Adversarial Networks :octocat: