890 Open source projects that are alternatives of or similar to Sign Language Gesture Recognition

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

Image Captioning using InceptionV3 and beam search

stock predict by cnn and lstm

Datasets, tools, and benchmarks for representation learning of code.

5th place solution for Kaggle competition Favorita Grocery Sales Forecasting

Pytorch Tutorial, Pytorch with Google Colab, Pytorch Implementations: CNN, RNN, DCGAN, Transfer Learning, Chatbot, Pytorch Sample Codes

SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach

End-to-end variable length Captcha recognition using CNN+RNN+Attention/CTC (pytorch implementation). 端到端的不定长验证码识别

RNN and general weights, gradients, & activations visualization in Keras & TensorFlow

코딩셰프의 3분 딥러닝, 케라스맛

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification

Part-of-Speech Tagger and custom implementations of LSTM, GRU and Vanilla RNN

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Music genre classification with LSTM Recurrent Neural Nets in Keras & PyTorch

A top-down, practical guide to learn AI, Deep learning and Machine Learning.

in progress

Code for Tensorflow Machine Learning Cookbook

A visualization tool for understanding and debugging RNNs

Sentiment Analysis with LSTMs in Tensorflow

Implementation of Neural Image Captioning model using Keras with Theano backend

Long short-term memory recurrent neural networks for learning peptide and protein sequences to later design new, similar examples.

Deepfakes Video classification via CNN, LSTM, C3D and triplets

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Hybrid Code Networks https://arxiv.org/abs/1702.03274

Augmenting word embeddings with their surrounding context using bidirectional RNN

language model in Chinese，基于Pytorch官方文档实现

Bitcoin price Prediction ( Time Series ) using LSTM Recurrent neural network

Implementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971

My Attempt(s) In The World Of ML/DL....

NN based lossless compression

A Bitcoin trade robot based on Tensorflow LSTM model.Just for fun.

Speech emotion recognition implemented in Keras (LSTM, CNN, SVM, MLP) | 语音情感识别

中文聊天机器人，基于10万组对白训练而成，采用注意力机制，对一般问题都会生成一个有意义的答复。已上传模型，可直接运行，跑不起来直播吃键盘。

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot

Sarcasm detection on tweets using neural network

Char-level RNN LSTM text generator📄.

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier

RNN(SimpleRNN, LSTM, GRU) Tensorflow2.0 & Keras Notebooks (Workshop materials)

Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)

The deeplearning algorithms implemented by tensorflow

Word Embedding + LSTM + FC

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

convolutional lstm implementation in pytorch

A minimum unofficial implementation of the "A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement" (CRN) using PyTorch

PyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks

Pytorch、Scikit-learn实现多种分类方法，包括逻辑回归（Logistic Regression）、多层感知机（MLP）、支持向量机（SVM）、K近邻（KNN）、CNN、RNN，极简代码适合新手小白入门，附英文实验报告（ACM模板）

基于RNN生成古诗

Scripts and tools to easily communicate with DeepGTAV. In the future a self-driving agent will be implemented.

Sentence Classifications with Neural Networks

Deep learning codes and projects using Python

Lightweight C++11 library for building deep recurrent neural networks

A pytorch implemention of "StyleNet: Generating Attractive Visual Captions with Styles"