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

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

Use tensorflow's tf.scan to build vanilla, GRU and LSTM RNNs

PyTorch tutorial for learners

Deep learning codes and projects using Python

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

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)

[Deprecated] Source Code Generation using Sequence Generative Adversarial Networks

Computer-generated poetry

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

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

Probabilistic Dialogue Act Classification for the Switchboard Corpus using an LSTM model

RMDL: Random Multimodel Deep Learning for Classification

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).

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

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.

A variational implementation of classical and quantum annealing using recurrent neural networks for the purpose of solving optimization problems.

<머신러닝 교과서 with 파이썬, 사이킷런, 텐서플로>의 코드 저장소

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

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press

Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks

Alternative approach for Adaptive Computation Time in TensorFlow

Sequence analyzing using Recurrent Neural Networks (RNN) based on Keras

Human activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).

The Official Deep Learning Framework for Route-based Place Recognition

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

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

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.

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

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.

Neural networks library for machine learning on PHP

Char-RNN implemented using TensorFlow.

3D reconstruction with neural networks using Tensorflow. See link for Video (https://www.youtube.com/watch?v=iI6ZMST8Ri0)

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

speech-to-text in pytorch

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

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

copper price(time series) prediction using bpnn and lstm

Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO

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

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

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

Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

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

Who Let The Dogs Out? Modeling Dog Behavior From Visual Data https://arxiv.org/pdf/1803.10827.pdf

PPPL deep learning disruption prediction package

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

A Python package for gender classification.

Tensorflow Implementation of Recurrent Convolutional Neural Network for Relation Extraction

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

ECG Classification

Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.

Application of machine learning to the Coinbase (GDAX) orderbook

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

Sentiment Analysis on the First Republic Party debate in 2016 based on Python,NLTK and ML.

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

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

CNN, LSTM, NBOW, fasttext 中文文本分类

Text Classification Algorithms: A Survey