A suite of PyTorch-based NLP models, including a name classifier, name generator, and French-to-English translator, built with RNN and sequence-to-sequence architectures.

This project is a Streamlit-powered app that predicts the next word in a given text sequence using RNN models (GRU and LSTM). Trained over 50 epochs, the GRU model achieved 70.89% training accuracy and 5.03% validation accuracy.

fantasy football performance predictor

Developing a PyTorch-based solution for predicting future values in financial time series data, leveraging RNNs and GRUs as part of the M3 competition for time series forecasting.

This repository contains three variants of a Sentiment Analysis model that uses a GRU (Gated Recurrent Unit) to predict the sentiment of a given text as either positive or negative. The models were built using PyTorch, and the training and testing data came from DLStudio

Image captioning with a benchmark of CNN-based encoder and GRU-based inject-type (init-inject, pre-inject, par-inject) and merge decoder architectures

Neural Networks project for Intelligent Systems course at Tecnico, Lisbon.

Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

Bachelor's thesis carried at Universitat Politecnica de Catalunya in partial fullfilment of the requirements for the degree in Telecommunications Technologies and Services Engineering

Official implementation for "CONVIQT: Contrastive Video Quality Estimator"

bike sharing prediction using recurrent neural network (RNN)-gated recurrent unit (GRU) implemented in python using the pytorch framework

Time Series Forecasting with Neural Networks

With an ever-increasing amount of astronomical data being collected, manual classification has become obsolete; and machine learning is the only way forward. Keeping this in mind, the LSST Team hosted the PLAsTiCC in 2018. This repository details our approach to this problem.

GRU DRNN model that generates classical music.

🔁Graphical models, Recurrent Neural Networks and SIFT algorithm for image processing, signal analysis and timeseries forecasting (MD Course: Intelligent Systems for Pattern Recognition)

Implementation of the paper "Show and Tell: A Neural Image Caption Generator" by Vinyals et al. (CVPR 2015)

Relationship Extraction using a Bi-directional GRU v/s CNN with multiple layers and max-pooling

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.

Predictes the posible full word based on given partial text.

Stock Price prediction for Yahoo Inc. using GRU (Gated Recurrant Units) in Keras. Predicting closing price for Yahoo stocks