Analyzing and predicting Google's stock prices through detailed data exploration and advanced LSTM models. This project involves data preprocessing, creating time-series sequences, constructing and training LSTM networks, and evaluating their performance to forecast future stock prices utilizing Python and Machine Learning libraries.

A fast, effective and accurate algorithm for univariate time series forecasting

This is the official implementation of our research paper "Non-residential electricity day ahead load forecasting using a Transformer based adversarial domain adaptation forecaster"

Personal projects

Machine learning research project predicting and identifying cyberattacks on the SWaT testbed from iTrust Centre Labs.

Trading Simulator to backtest RSI strategies, optimize parameters, and predict future stock prices with LSTM

A bangla chatbot using bidirectional lstm

A Novel Approach leveraging Auto-Encoders, LSTM Networks and Maximum Entropy Principle for Video Super-Resolution (Upscaling and Frame Interpolation)

This project aims to develop a machine learning application for water quality analysis.

This notebook loads a time series of gas concentrations in the air to train a recurrent neural network to predict the next hour of data

Deep Learning based Weather Prediction

Sales Time Series with XGBoost and Neural Networks

LSTM Model built from scratch and trained on custom generated synthetic health data

MSc project investigating multi-modal fusion approaches to combining textual and visual features for multi-page classification of documents within the OGA National Data Repository (NDR).

Neural Network that is able to translate any sign language into text.

A repo consisting of my source code and resources for my Research Paper regarding LSTM models and Stock Price predictions

Time series forecasting with TensorFlow

A project that involves using Deep Learning to forecast stock prices.