Time Series Forecasting with Neural Networks

Recurrent Neural Networks (RNN's) for sentiment analysis on IMDB dataset from keras....

Opinion recommendation is a task, recently introduced, for consistently generating a text review and a rating score that a certain user would give to a certain product, which has never seen before. Input information driving recommendation is text reviews and ratings for this product contributed by other users and text reviews submitted by the us…

Deep Learning class projects from Kagle. All projects are individual projects conducted by me using pyhton (keras, tensor-flow, matplotlib and other libraries). Different Deep Neural Network (DNN) methods were used and results were compared based one efficiency and accuracy. Results and conclusions based on results were reported.

Simulation of "Triggering Proactive Business Process Adaptations via Online Reinforcement Learning" paper with proper steps and recreating the results

Framework for learning effective reduced order dynamics of molecular systems.

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 is a practical implementation implementing neural networks on top of fasttext as well as word2vec word embeddings.

LSTM based Model for Real-time Stock Market Prediction on Unexpected Incidents

Hybrid Question Answering System project, based on SQuAD Dataset.

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

Codes for EEE 443 Neural Networks Projects

This repository includes a reinforcement learning framework for solving the tactical decision-making problem subject to cross-country soaring (by the example of the competition task of GPS Triangle racing).

Prediction of a star light curve behaviour with a neural network

This is a code repository for my semester project for CSCI 8980 Perception & Learning in Field Robotics, taught by Dr. Junaed Sattar in the Fall of 2021, at the University of Minnesota, Minneapolis, MN, USA.

Project aims to forecast potato prices in India using LSTM, KNN, and Random Forest Regression, integrating historical data on prices, regional stats, and rainfall patterns. Targeting agricultural stakeholders for informed decision-making.

Hybrid Question Answering System project, based on SQuAD Dataset

This is a Stock Prediction project in which i predict the stocks of Tata Steel Stock dataset (2015-2021). I used python and it's libraries to perform this project like Pandas, Numpy, sklearn etc. I used LSTM for predict prices of the stocks.

Compare SVM mode yoga movement classification accuracy with Linear kernel, Polynomial kernel, RBF (Radial Basis Function) kernel, LSTM with accuracy up to 98%. In addition, it also supports adjusting the practitioner's movements according to standard movements.

Online quality of service prediction