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

PyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks

基于RNN生成古诗

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

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

A visualization tool for understanding and debugging RNNs

Application of machine learning to the Coinbase (GDAX) orderbook

Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems

CNN, LSTM, NBOW, fasttext 中文文本分类

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch. Based on code of https://github.com/karpathy/char-rnn. Support Chinese and other things.

Natural Language Processing with TensorFlow, published by Packt

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.

🔬 Nano size Theano LSTM module

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

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)

Nested LSTM Cell

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

Efficient, transparent deep learning in hundreds of lines of code.

[PAMI 2021] Gating Revisited: Deep Multi-layer RNNs That Can Be Trained

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

A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.

中文古诗自动作诗机器人，屌炸天，基于tensorflow1.10 api，正在积极维护升级中，快star，保持更新！

Predict Cryptocurrency Price with Deep Learning

copper price(time series) prediction using bpnn and lstm

基於DA-RNN之DSTP-RNN論文試做(Ver1.0)

GPU/CPU (CUDA) Implementation of "Recurrent Memory Array Structures", Simple RNN, LSTM, Array LSTM..

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

Enhanced BiLSTM Inference Model for Natural Language Inference

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

Electric load forecast using Long-Short-Term-Memory (LSTM) recurrent neural network

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

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

LSTM, GRU cell implementation from scratch in tensorflow

Implementing different RNN models (LSTM,GRU) & Convolution models (Conv1D, Conv2D) on a subset of Amazon Reviews data with TensorFlow on Python 3. A sentiment analysis project.

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

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.

[AAAI 2020] Modeling Personality with Attentive Networks and Contextual Embeddings

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

CPU and GPU implementations of some 2D RNN layers

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

分别使用rnn/cnn/rcnn来实现根据患者描述，进行疾病诊断

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

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

Sentiment Analysis with LSTMs in Tensorflow

End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

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

A collection of UNet and hybrid architectures in PyTorch for 2D and 3D Biomedical Image segmentation

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

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

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。

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.

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

A PyTorch Tutorials of Sentiment Analysis Classification (RNN, LSTM, Bi-LSTM, LSTM+Attention, CNN)

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

Stock Price Prediction using Machine Learning Techniques

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

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

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.

Chatbot in 200 lines of code using TensorLayer