584 Open source projects that are alternatives of or similar to See Rnn

Haste: a fast, simple, and open RNN library

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Keras tutorial for beginners (using TF backend)

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

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

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

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.

Word Embedding + LSTM + FC

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

Deep Learning

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

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Tensorflow Implementation of Densely Connected Bidirectional LSTM with Applications to Sentence Classification

CNN, LSTM, NBOW, fasttext 中文文本分类

My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

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Char-level RNN LSTM text generator📄.

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

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PyTorch tutorial for learners

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

🔬 Nano size Theano LSTM module

Implementation of the paper - Generative Recurrent Networks for De Novo Drug Design.

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

Multi-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.

CPU and GPU implementations of some 2D RNN layers

Sequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.

分别使用rnn/cnn/rcnn来实现根据患者描述，进行疾病诊断

rnn trained on r/totallynotrobots 🤖

Pull stock prices from online API and perform predictions using Long Short Term Memory (LSTM) with TensorFlow.js framework

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

language models toolkits with hierarchical softmax setting

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

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.

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

BasicOCR是一个致力于解决自然场景文字识别算法研究的项目。该项目由长城数字大数据应用技术研究院佟派AI团队发起和维护。

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An extension on the Hierachical Recurrent Encoder-Decoder for Generative Context-Aware Query Suggestion, our implementation is in Tensorflow and uses an attention mechanism.

Easy-to-use Deep LSTM Neural Network to generate song sounds like containing improvisation.

Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.

Tutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101

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.

Stock Price Prediction using Machine Learning Techniques

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A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

Sentiment Analysis with LSTMs in Tensorflow

🎵 Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

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

Chatbot in 200 lines of code using TensorLayer

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

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.

All about Neural Networks!

Application of machine learning to the Coinbase (GDAX) orderbook