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Abdullah Tarek's Projects

ab-testing icon ab-testing

This is a Data analytics nano degree project where I made an AB test to figure out whether an eCommerce company implement this new page or keep the old one.

bert_score icon bert_score

This repo computes arabert with arabert's integration

disaster_response_pipeline icon disaster_response_pipeline

An ETL and machine learning pipeline that performs a multi label classification of messages to a disaster category using NLP and machine learning

dog_breed_webapp icon dog_breed_webapp

A webapp that detects dog breeds when given an image using keras, python,flask

early-detection-of-lung-cancer-using-machine-learning icon early-detection-of-lung-cancer-using-machine-learning

Early detecting of lung cancer using the Luna data set with LIDC IDRI annotations using two models nodule classification"Googlent model" and the malignancy classification "Lenet model". This was for kaggle's Data science bowl 2017.

etherscan_scraping icon etherscan_scraping

This project scraps and stores transaction data of the top 1000 of a given crypto-currency from the etherscan website and stores it in a MySQL database using python

football_analysis icon football_analysis

This repository contains a comprehensive computer vision/machine learning football project that uses YOLO for object detection, Kmeans for pixel segmentation, optical flow for motion tracking, and perspective transformation to analyze player movements in football videos

nlp_classifier icon nlp_classifier

This is a general repo that helps you develop fast/effective NLP classifiers using Huggingface

private-ai icon private-ai

This is my solutions to the notebooks of Udacity's Secure and Private AI course

red_wine_quality-eda icon red_wine_quality-eda

This is one of udacity's Data analytics nano degree project where I practice my EDA skills on a kaggle dataset using R.

slam icon slam

landmark detection and tracking (SLAM)

tennis_analysis icon tennis_analysis

This project analyzes Tennis players in a video to measure their speed, ball shot speed and number of shots. This project will detect players and the tennis ball using YOLO and also utilizes CNNs to extract court keypoints. This hands on project is perfect for polishing your machine learning, and computer vision skills.

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