junayed-hasan

Quantum-Machine-Learning-Qiskit-PyTorch

This repository contains codes and tutorials for quantum machine learning using PyTorch and Qiskit. It covers topics such as qiskit basics, deep learning fundamentals, and hybrid quantum-classical models. It also demonstrates how to use TorchQuantum, a PyTorch-based framework for quantum neural networks.

Deep-Learning-PyTorch

This repo contains jupyter notebooks that show how to use PyTorch for various deep learning tasks, such as image classification, object detection, NLP, and more. The notebooks cover data loading, model building, training, evaluation, and advanced techniques.

Adult-Income-Prediction-Machine-Learning

Quantum-Machine-Learning

Codes for the research article on Knowledge Transfer from Classical to Quantum Neural Networks Using Knowledge Distillation

Clinical-Language-Model-Distillation-Pruning-Quantization

OptimCLM enhances clinical decision-making and management by optimizing clinical language models for patient outcome predictions, achieving up to 22.88× compression and 28.7× speedup with minimal performance loss, using techniques like knowledge distillation, pruning, and quantization on MIMIC-III data.

LLM-Aggregated-Ensemble-Clinical-Outcomes

Codes for the research article "Preserving the knowledge of long clinical texts using aggregated ensembles of large language models"

code_snippets

CrazyCrawler

A website which works as a search engine and enables users to scrape and crawl data from websites. Built using Django framework with HTML, CSS, JS and mySQL database. Android app built using Android Studio.

Help-The-Needy

An online donation system to help the poor people at remote areas of Bangladesh.

KD-LLM-Clinical-Outcomes

Codes for the research article "Distilling the Knowledge of Clinical Outcome Predictions in Large Language Models for Resource Constrained Healthcare Systems"

junayed-hasan/Clinical-Language-Model-Distillation-Pruning-Quantization

OptimCLM enhances clinical decision-making and management by optimizing clinical language models for patient outcome predictions, achieving up to 22.88× compression and 28.7× speedup with minimal performance loss, using techniques like knowledge distillation, pruning, and quantization on MIMIC-III data.

junayed-hasan/Deep-Learning-PyTorch

This repo contains jupyter notebooks that show how to use PyTorch for various deep learning tasks, such as image classification, object detection, NLP, and more. The notebooks cover data loading, model building, training, evaluation, and advanced techniques.

junayed-hasan/spontaneous-smile-recognition

Codes and implementation details for spontaneous smile recognition

junayed-hasan/Adult-Income-Prediction-Machine-Learning

junayed-hasan/Quantum-Machine-Learning-Qiskit-PyTorch

This repository contains codes and tutorials for quantum machine learning using PyTorch and Qiskit. It covers topics such as qiskit basics, deep learning fundamentals, and hybrid quantum-classical models. It also demonstrates how to use TorchQuantum, a PyTorch-based framework for quantum neural networks.

junayed-hasan/CrazyCrawler

A website which works as a search engine and enables users to scrape and crawl data from websites. Built using Django framework with HTML, CSS, JS and mySQL database. Android app built using Android Studio.

junayed-hasan/KD-LLM-Clinical-Outcomes

Codes for the research article "Distilling the Knowledge of Clinical Outcome Predictions in Large Language Models for Resource Constrained Healthcare Systems"

junayed-hasan/LLM-Aggregated-Ensemble-Clinical-Outcomes

Codes for the research article "Preserving the knowledge of long clinical texts using aggregated ensembles of large language models"

junayed-hasan/Quantum-Machine-Learning

Codes for the research article on Knowledge Transfer from Classical to Quantum Neural Networks Using Knowledge Distillation

junayed-hasan/Machine_Learning

CSE445 Machine Learning Resources

junayed-hasan/Help-The-Needy

An online donation system to help the poor people at remote areas of Bangladesh.

junayed-hasan/code_snippets