rnn-model

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.

Text classification using deep learning models in Pytorch

Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch

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 R/Shiny app for interactive RNN tensorflow models

I used in this project a reccurent neural network to generate c code based on a dataset of c files from the linux repository.

A food ordering android application with feedback analyzer to improve food suggestions to customer.

generate captions for images using a CNN-RNN model that is trained on the Microsoft Common Objects in COntext (MS COCO) dataset

Recurrent Neural Network (LSTM) by using TensorFlow and Keras in Python for BitCoin price prediction

Price Prediction Case Study predicting the Bitcoin price and the Google stock price using Deep Learning, RNN with LSTM layers with TensorFlow and Keras in Python. (Includes: Data, Case Study Paper, Code)

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System.

Deep Learning notes and practical implementation with Tensorflow and keras. Text Analytics and practical application implementation with NLTK, Spacy and Gensim.

Sinhalese Language based Hate Speech Detection

Time series forecasting using RNN, Twitter Sentiment Analysis and Turtle Trading Strategy applied on Cryptocurrency

Event-based neural networks

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System. The deployed project link is as follows.

A QA System based by BiLSTM. 一个基于双向LSTM的智能问答系统，有交互界面、详细注释、多版本、能运行、文件齐全。

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning, Recurrent Neural Network models, MERN web I/O System.

Annabelle the noob. An experimental, incomplete(at present) chatbot.