In PyTorch Learing Neural Networks Likes CNN(Convolutional Neural Networks for Sentence Classification (Y.Kim, EMNLP 2014) 、LSTM、BiLSTM、DeepCNN 、CLSTM、CNN and LSTM

Text classification using deep learning models in Pytorch

Deep Learning models for network traffic classification

A LSTM model using Risk Estimation loss function for stock trades in market

Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences (NIPS 2016) - Tensorflow 1.0

AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.

LSTM-based Models for Sentence Classification in PyTorch

Highway Networks implement in pytorch

Hierarchical Attention Network for Document Classification

Python based Quant Finance Models, Tools and Algorithmic Decision Making

[deprecated] reference code for string segmentation using LSTM(tensorflow)

Stock Market Predictor with LSTM network. Web scraping and analyzing tools (ohlc, mean)

基于GPT-2和LSTM的歌词和说唱歌词创作

time-series prediction for predictive maintenance

Time-series prediction with LSTNet in Apache MXNet Gluon

Virtual walks in Google Street View using PoseNet and applying Deep Learning models to recognize actions.

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

This repository contains programming assignments and research paper refrenced in the deeplearning.ai specialization by Andrew-Ng on Coursera.

Topics related to Deep Learning

An implementation of the grid LSTM network for PyTorch

My solution for Quora's Question Pair contest on Kaggle.

The LSTM model generates captions for the input images after extracting features from pre-trained VGG-16 model. (Computer Vision, NLP, Deep Learning, Python)

Building an LSTM Recurrent Neural Network for Predicting Stock Market Prices.

Find the origin of words in every language using a Deep Neural Network trained to create an etymological map.

Piano music generation with RNN with Tensorflow

Sequence Labeling implemented by BiLSTM using Tensorflow

Discord Bot in python with rasa nlu, tensorflow, discord api

The aim of this project is to generate text using LSTM Recurrent Neural Networks. LSTM Recurrent Neural Networks are powerful Deep Learning models that are used for learning sequenced data. Here a LSTM model is trained on 200 million samples, and the idea is that after training on 200 million samples, it should be able to generate text.

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