472 Open source projects that are alternatives of or similar to Easyesn

SimpleDNN is a machine learning lightweight open-source library written in Kotlin designed to support relevant neural network architectures in natural language processing tasks

Text classifier for Hierarchical Attention Networks for Document Classification

using rnn (lstm or gru) and ctc to convert line image into text, based on torch7 and warp-ctc

Machine Reading Comprehension in Tensorflow

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

All about Neural Networks!

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

A project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.

CNN, LSTM, NBOW, fasttext 中文文本分类

Text Classification Algorithms: A Survey

rnn based model for recommendations

Overview of Modern Deep Learning Techniques Applied to Natural Language Processing

List of papers, code and experiments using deep learning for time series forecasting

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

Deep-Plant: Plant Classification with CNN/RNN. It consists of CAFFE/Tensorflow implementation of our PR-17, TIP-18 (HGO-CNN & PlantStructNet) and MalayaKew dataset.

R interface to the keras library

Deep learning for price movement prediction using high frequency limit order data

PPPL deep learning disruption prediction package

A Recurrent Neural Network to predict Bitcoin value

Some of the ML and DL related reading materials, research papers that I've read

Sentiment Analysis with LSTMs in Tensorflow

Tensorflow Implementation of Recurrent Convolutional Neural Network for Relation Extraction

For recognising hand gestures using RNN and LSTM... Implementation in TensorFlow

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

Deepfakes Video classification via CNN, LSTM, C3D and triplets

Application of machine learning to the Coinbase (GDAX) orderbook

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

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

Named Entity Recognition with RNN, implemented by Chainer

A TensorFlow implementation of the collaborative RNN (Ko et al, 2016).

An implementation of RNN-RBM & GBRBM.

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

Chatbot in 200 lines of code using TensorLayer

论文“Attention-over-Attention Neural Networks for Reading Comprehension”中AoA模型实现

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

TensorFlow and Deep Learning Tutorials

Event-based music generation with RNN using PyTorch

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

Tensorflow implementation of attention mechanism for text classification tasks.

RNN based Time-series Anomaly detector model implemented in Pytorch.

Handwritten Text Recognition (HTR) system implemented with TensorFlow.

Code for Tensorflow Machine Learning Cookbook

Quantize weights and activations in Recurrent Neural Networks.

Stock Price Prediction using Machine Learning Techniques

Image Captioning: Implementing the Neural Image Caption Generator with python

Visualizing RNNs using the attention mechanism

Sequence to Sequence Models with PyTorch

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

CS224n: Natural Language Processing with Deep Learning Assignments Winter, 2017

WTTE-RNN a framework for churn and time to event prediction

Implementation of Simple Recurrent Unit in Keras

TensorFlow Tutorial for Time Series Prediction

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.

RNN-based generative models for speech.

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

Machine Learning on Sequential Data Using a Recurrent Weighted Average

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.

videos, lectures, blogs for Deep Learning

Biologically-realistic recurrent convolutional neural networks

Quasi-recurrent Neural Networks for Keras