Hena Ghonia (Hstellar)

Hstellar

Geek Repo

Location:Toronto

Home Page:hstellar.github.io

Twitter:@hena_ghonia

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Hena Ghonia's repositories

Game_controller_arduino

Created a game using the Unity 3D engine and a hand control device consisting of a MPU6050 Accelerometer and an Arduino UNO to control the movements of the game objects.

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ML-Age-estimation-from-facial-images

Examining ‘wrinkles’ as a feature on facial images and making use of fuzzy C-means clustering to estimate age using Matlab.

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Human_Activity_Recognition

Human Activity Recognition using smartphone dataset

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Face-recognition-Challenge

Face recognition is implemented using SIFT features from facial images and then classifying by Support vector machine.

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Conversational_Question_Anwering_System

This repository contains various methods such as FlowQA, GraphFlow and BERT based models for conversational Q&A system

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Detection-of-extreme-weather-events

Classification of extreme weather events

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FHIR_Hack

Problem statement: To analyze diseases considering diet intake and demographic features from National Health and Nutrition Examination Survey (NHANES) which is major program of the National Center for Health Statistics (NCHS). The survey combines interviews and physical examinations. NCHS is part of Centers for Disease Control and Prevention and has the responsibility for producing vital and health statistics for the Nation.

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Active-DKL

Contains short paper accepted at Collas'23 Workshop track

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IFT-6135

Contains code and assignment solution for course IFT 6135 taught by Aaron Courville

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Covid_immunology_appathon_streamlit

To explore the relationship between personalized immune repertoires and COVID-19 disease variables and associated factors

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CUDAMasterclass

Code base for CUDA Masterclass course

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GraphFlow

Code & data accompanying the IJCAI 2020 paper "GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension"

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Hstellar.github.io

Your favorite AnchorCMS theme, now for Jekyll!

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PySyft

A library for encrypted, privacy preserving deep learning

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