There are 2 repositories under rnn-model topic.
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
Event-based neural networks
Time series forecasting using RNN, Twitter Sentiment Analysis and Turtle Trading Strategy applied on Cryptocurrency
Annabelle the noob. An experimental, incomplete(at present) chatbot.
An AI chatbot built using SEQ2SEQ Model
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.
基于tensorflow搭建的神经网络recursive autuencode,用于实现句子聚类
A repository for my pytorch models
Deep Learning, Attention, Transformers, BERT, GPT-2, GTP-3
Built RNNs that can generate sequences based on input data - with a focus on two applications: used real market data in order to predict future Apple stock prices using an RNN model. The second one will be trained on Sir Arthur Conan Doyle's classic novel Sherlock Holmes and generates wacky sentences based on it that may - or may not - become the next great Sherlock Holmes novel.
make stock prediction model using Tensorflow, Python and web crawling
Generalized Implementation of RNNs for Chaotic Time Series Prediction
Depression detection from social media
Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning, Recurrent Neural Network models, MERN web I/O System.
Piano music generation with RNN with Tensorflow
Time-series analysis of the electricity load consumption in the Mumbai Metropolitan Region.
Analyze and classify videos in the UCF101 dataset
Song lyrics generation using Recurrent Neural Networks (RNNs)
个人实现pytorch高级编程,包括基本知识、卷积神经网络、循环神经网络、生成对抗、模型部署和分布式训练(2022)
Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System.
Solar Irradiance Forecasting Using Deep Learning Techniques