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

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

Tutorial: Multi-layer Recurrent Neural Networks (LSTM, RNN) for text models in Python using TensorFlow.

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.

RNN benchmarks of pytorch, tensorflow and theano

The RWTH extensible training framework for universal recurrent neural networks

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

TensorFlow implementation of Independently Recurrent Neural Networks

My bachelor's thesis—analyzing the application of LSTM-based RNNs on financial markets. 🤓

Chainer implementation of Deepmind's Visual Attention Model paper

A deep learning library to provide algs in pure Numpy or Tensorflow.

R interface to the keras library

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

TensorFlow implementation of "Tracking the World State with Recurrent Entity Networks".

Codes and Templates from the SuperDataScience Course

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

A Neural Network based Chatbot

Experiment diverse Deep learning models for music generation with TensorFlow

PPPL deep learning disruption prediction package

Tensorflow implementation of "Tracking the World State with Recurrent Entity Networks" [https://arxiv.org/abs/1612.03969] by Henaff, Weston, Szlam, Bordes, and LeCun.

The source of the IJCAI2017 paper "Modeling Trajectory with Recurrent Neural Networks"

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

此项目致力于构建一套最基础，最精简，可维护的react-native项目，支持ios，android 🌹

Jupyter notebooks for Chainer hands-on

Generalised and highly customisable, hybrid-parallelism, database based, deep learning framework.

A Recurrent Neural Network to predict Bitcoin value

TensorFlow Implementation of TCN (Temporal Convolutional Networks)

Differentiable Neural Computers, Sparse Access Memory and Sparse Differentiable Neural Computers, for Pytorch

Thai Word Segmentation and Part-of-Speech Tagging with Deep Learning

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

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

Machine learning models for time series analysis

Source code of the model used in Tensorflow Speech Recognition Challenge (https://www.kaggle.com/c/tensorflow-speech-recognition-challenge). The solution ranked in top 5% in private leaderboard.

Sentiment Analysis with LSTMs in Tensorflow

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

Neural Network for HFT-trading [experimental]

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.

Tensorflow Implementation of Recurrent Convolutional Neural Network for Relation Extraction

机器学习、深度学习、NLP实战项目

Code base for solving Markov Decision Processes and Reinforcement Learning problems using Recurrent Convolutional Neural Networks.

Online Handwriting Signature Verification using CNN + RNN.

A fast implementation of Neural Image Caption by Chainer

Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement …

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

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

Code and Data to accompany "Dilated Convolutions for Modeling Long-Distance Genomic Dependencies", presented at the ICML 2017 Workshop on Computational Biology

Deep learning driven jazz generation using Keras & Theano!

Deepfakes Video classification via CNN, LSTM, C3D and triplets

Pytorch implementation of CRNN (CNN + RNN + CTCLoss) for all language OCR.

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

Nested LSTM Cell

Application of machine learning to the Coinbase (GDAX) orderbook

A bidirectional recurrent neural network model with attention mechanism for restoring missing punctuation in unsegmented text

Projects from the Deep Learning Specialization from deeplearning.ai provided by Coursera

Deep Learning neural network for correcting spelling

Recurrent (conditional) generative adversarial networks for generating real-valued time series data.

Online Hand Writing Recognition using BLSTM

The official repository for our paper "Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks". We develop a method for analyzing emerging functional modularity in neural networks based on differentiable weight masks and use it to point out important issues in current-day neural networks.

A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea.

Malicious URL detector using keras recurrent networks and scikit-learn classifiers

Train LSTM to writer novel (HongLouMeng here) in Pytorch.