There are 2 repositories under gated-recurrent-unit topic.
Patient2Vec: A Personalized Interpretable Deep Representation of the Longitudinal Electronic Health Record
Named Entity Recognition (NER) with different combinations of BiGRU, Self-Attention and CRF
Implementing different RNN models (LSTM,GRU) & Convolution models (Conv1D, Conv2D) on a subset of Amazon Reviews data with TensorFlow on Python 3. A sentiment analysis project.
Predict the next 24 hours' temperatures by GRU and Transformer
Sequence Models repository for all projects and programming assignments of Course 5 of 5 of the Deep Learning Specialization offered on Coursera and taught by Andrew Ng, covering topics such as Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Long Short Term Memory (LSTM), Natural Language Processing, Word Embeddings and Attention Model.
Next–Generation Intrusion Detection for IoT EVCS: Integrating CNN, LSTM, and GRU Models
Named Entity Recognition - Python - Keras
STM32F429 Online handwritten character classification with Gated Recurrent Unit Neural Network
CoreML compatible GRU neural network for dynamic prediction
Created AI models to forecast Wallmart's sales. Used different models, like dense, LSTM, GRU and naive model. Different window and horizon sizes are used too. Compared models visually at the end.
Sentiment Analysis attempt and comparison in chess.com play store review using multiple algorithm and feature extraction
Deep Learning in python
This repository contains notes, slides, labs, assignments and projects for the Deep Learning Specialization by DeepLearning.AI and Coursera.
Code for Multi-dimensional Gated Recurrent Units for the Segmentation of Biomedical Data
Recurrent neural network with GRUs for trigger word detection from an audio clip
I constructed a knowledge graph of stakeholders of Bavarian state ministries and used network analysis to calculate statistics. Furthermore time-series feature forecasting and topological link prediction was employed to analyze the evolution of the network.
This repository includes course assignments of Natural Language Processing in TensorFlow on Coursera by DeepLearning.AI
Participants in this Specialization have the opportunity to construct and train various neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Transformers. They learn to enhance these networks with techniques such as Dropout, BatchNorm, Xavier/He initialization, among others.
Implementation of LSTM time series tuned with GRU.
Deep Learning Machine Learning Templates
Codes for EEE 443 Neural Networks Projects
Implementation of the model inversion attack on the Gated-Recurrent-Unit neural network
Repository for Deep Learning Fundamentals Assignment 3: RNN for Stock Price Prediction
Microsoft Stock Deep Learning Model Prediction and Story Timeline Analysis.
This repository contains a prediction model and simple analysis tool for dogecoin price movements using Gated Recurrent Units (GRU). The dataset used is daily Dogecoin from 25 December 2017 to 31 December 2024 (7 years 1 week) which is recorded every day.
Algorithm to convert between various languages with the help of NLP techniques
LSTM vs GRU
Introductory-Gru
This project aims to develop a deep learning model for predicting the next word in a given sequence of words. The model is built using LSTM and GRU networks, which are well-suited for sequence prediction tasks