In PyTorch Learing Neural Networks Likes CNN、BiLSTM

Text classification using deep learning models in Pytorch

Deep Learning models for network traffic classification

Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting

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

Acquiring data from Alpha Vantage and predicting stock prices with PyTorch's LSTM

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

基于tensorflow lstm模型的彩票预测

First Version.. Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT

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

A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach

Lyrics and rap lyrics AI-generate system based on GPT-2 and LSTM / 基于GPT-2和LSTM的歌词和说唱歌词创作系统

A recurrent (LSTM) neural network in C

lstm-rnn, seq2seq model and attention-seq2seq model for vessel trajectory prediction.

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

LSTM-based Models for Sentence Classification in PyTorch

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

Highway Networks implement in pytorch

The aim of this repository is to show a baseline model for text classification by implementing a LSTM-based model coded in PyTorch. In order to provide a better understanding of the model, it will be used a Tweets dataset provided by Kaggle.

time-series prediction for predictive maintenance