Name: Amaan Izhar
Type: User
Company: Master's of Computer Science Student @ University of Malaya
Bio: Machine/Deep Learning, Computer Vision, Natural Language Processing, Multimodality, AI in Medicine
Location: Kuala Lumpur, Malaysia
Amaan Izhar's Projects
An end to end machine learning project for evaluating acceptability of a car based on various features.
It is a full-stack blog web application built with React on the frontend and Django/DRF on the backend integrated with AWS-S3 & AWS-RDS services.
A machine learning project on an imbalanced credit card data that detects fraudulent transactions.
An end to end deep learning project made by using streamlit for predicting handwritten drawn digits/alphabets via CNN & ANN.
A big data project where PySpark was utilized in a binary classification as well as clustering task.
A text-based simulation of the operation of a n-bit binary adder and subtractor using full adder circuit to add/subtract two positive integer numbers.
Usage of numerical analysis techniques to solve and demonstrate the Google pagerank problem.
A full stack desktop app serving as a KFUPM club management system.
The KFUPM Community App streamlines communication between community members and enable them to seek assistance for household chores, get notified of public events/emergencies, buy-sell second-hand products and much more.
Binary classification of lumpy skin disease (imbalanced dataset) using ML algorithms in addition to oversampling/undersampling techniques.
It is a desktop GUI application.
A deep learning project for detecting weather conditions in the Middle Eastern region from RGB images.
A simple semi-autoML web app designed for beginners.
A REST API for 2 NLP models that exercise binary and multilabel classification of text.
It is a full-stack note-taking web application built with React on the frontend and Django/Django-Rest-Framework on the backend.
N-Queens GUI solver using A* (A-Star) and Genetic Algorithm.
An attempt to predict poker hands using machine and deep learning techniques in addition to a manual coded method.
Official implementation of our paper - R2GMedS: Radiology Report Generation with Stacked Medical Signals of Contextual Biomedical Entities and Auxiliary Knowledge
It is a desktop GUI application for a visually traceable Trie data structure.
An encoder-decoder deep learning model (with/without attention mechanism) where the input is an arabic sign-language video and the output is its translation in text format.