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.
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Updated
Apr 25, 2024 - Python
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.
🛡️ A GRU deep learning system against attacks in Software Defined Networks (SDN).
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
Details of certified courses covered by me. Includes notes and solutions to programming exercises.
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.
doctor_prescription_recognization_using_DeepLearning project for epics
👾 Specialization on Deep Learning with TensorFlow on Coursera offered by DeepLearning.AI
Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification
Triplet Loss Based User Analysis
Pytorch implementation of a GRU-based RNN for Sentiment Analysis in Mental Disorder Online Communitites.
An implementation of classical GRU (Cho, el at. 2014) along with Optimized versions (Dey, Rahul. 2017) on TensorFlow that outperforms Native tf.keras.layers.GRU(units) implementation of Keras.
We use machine learning tools to predict the price of ethereum from historical data, economic indicators, and community sentiment on ethereum specifically from twitter.
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"
Estimating the growth or depreciation on exchange rates by using sentiment analysis method from social media comments
bike sharing prediction using recurrent neural network (RNN)-gated recurrent unit (GRU) implemented in python using the pytorch framework
Comparing Long Term Short Memory (LSTM) & Gated Re-current Unit (GRU) during forecasting of oil price .Exploring multivariate relationships between West Texas Intermediate and S&P 500, Dow Jones Utility Avg, US Dollar Index Futures , US 10 Yr Treasury Bonds , Gold Futures.
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