306 Open source projects that are alternatives of or similar to STAR_Network

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

Deep Learning

This is my graduation project in BIT. Title: Noise Reduction Using GRU.

Load forcasting on Delhi area electric power load using ARIMA, RNN, LSTM and GRU models

AI Exercise Rep Counter based on Google's Human Pose Estimation Library (Posenet)

Porting of Skip-Thoughts pretrained models from Theano to PyTorch & Torch7

Word Embedding + LSTM + FC

Generating Pokemon cards using a mixture of StyleGAN and RNN to create beautiful & vibrant cards ready for battle!

Recurrent Neural Networks (RNN, GRU, LSTM) and their Bidirectional versions (BiRNN, BiGRU, BiLSTM) for word & character level language modelling in Theano

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

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.

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

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

Keras tutorial for beginners (using TF backend)

ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

[RSE21] Pytorch code for hierarchical time series classification with multi-stage convolutional RNN

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

RNN(LSTM, GRU) in Theano with mini-batch training; character-level language models in Theano

Haste: a fast, simple, and open RNN library

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

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

In these notebooks the entire research and implementation process carried out for the construction of various machine learning models based on neural networks that are capable of predicting levels of solar radiation is captured given a set of historical data taken by meteorological stations.

CNN, RNN, and Bayesian NN classification for ECG time-series (using TensorFlow in Swift and Python)

Recurrent Additive Networks for Tensorflow

Inspired by the neural style algorithm in the computer vision field, we propose a high-level language model with the aim of adapting the linguistic style.

Recurrent Neural Network (LSTM) by using TensorFlow and Keras in Python for BitCoin price prediction

A siamese LSTM to detect sentence/question pairs.

THEANO-KALDI-RNNs is a project implementing various Recurrent Neural Networks (RNNs) for RNN-HMM speech recognition. The Theano Code is coupled with the Kaldi decoder.

light deep neural network tools box(LSTM,GRU,RNN,CNN,Bi-LSTM,etc)

In PyTorch Learing Neural Networks Likes CNN(Convolutional Neural Networks for Sentence Classification (Y.Kim, EMNLP 2014) 、LSTM、BiLSTM、DeepCNN 、CLSTM、CNN and LSTM

Online Handwriting Signature Verification using CNN + RNN.

Neural Machine Translation with Keras

Predict Cryptocurrency Price with Deep Learning

百度云魅族深度学习应用大赛

🔬 Nano size Theano LSTM module

Project 4 for Metis bootcamp. Objective was generation of character-level RNN trained on Donald Trump's statements using Keras. Also generated Markov chains, and quick pyTorch RNN as baseline. Attempted semi-supervised GAN, but was unable to test in time.

A toolkit for neural language modeling using Tensorflow including basic models like RNNs and LSTMs as well as more advanced models.

This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.

Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow

The project uses state of the art deep learning on collected data for automatic analysis of emotions.

📓 Notes for Andrew Ng's courses on deep learning

Implementation of Hierarchical Attention Networks in PyTorch

language models toolkits with hierarchical softmax setting

A Keras library for multi-step time-series forecasting.

机器学习、深度学习、NLP实战项目

🧠👨‍💻Deep Learning Specialization • Lecture Notes • Lab Assignments

Tensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification

Keras and PyTorch implementations of the MaLSTM model for computing Semantic Similarity.

An RNN (GRU) TensorFlow Android App for word prediction.

LSTM, GRU cell implementation from scratch in tensorflow

CIKM AnalytiCup 2017 is an open competition that is sponsored by Shenzhen Meteorological Bureau, Alibaba Group and CIKM2017. Our team got the third place in the first phrase. And in the second phrase we got the fourth place.

Official repo of the article: Yousef, W. A., Ibrahime, O. M., Madbouly, T. M., & Mahmoud, M. A. (2019), "Learning meters of arabic and english poems with recurrent neural networks: a step forward for language understanding and synthesis", arXiv preprint arXiv:1905.05700

Relation Classification - SEMEVAL 2010 task 8 dataset

An experimental web text editor that runs a LSTM model while you write to suggest new lines

Traffic Flow Prediction with Neural Networks(SAEs、LSTM、GRU).

Application of machine learning to the Coinbase (GDAX) orderbook

bitcoin prediction algorithms

TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction

My implementation of "Hierarchical Attention Networks for Document Classification" in Keras

Detecting and Predicting Forest Cover Change in Pakistani Areas Using Remote Sensing Imagery