About Me

Good experience with Data Science, made many projects and used many different algorithms on different datasets good experience with Machine learning and Data analysis, NLP, good experience with Transformer Model, I have experience with Computer Vision, and I also have good experience with Software engineering (backend with Laravel) I made many projects based on DB by using MySQL. Bachelor of computer science, And I am Notebook expert on Kaggle.

Education

Bachelor of Computer Science 2022

El shrouk academy for computer and information science

Experience

Junior AI & DS Engineer

Developed machine learning models for predictive analysis...

Skills

• Python, TensorFlow, Keras, Machine learning,Deep learning, NLP, Computer Vision, pandas, power bi, scikit-learn
• Laravel, PHP, MySQL, MOngoDB
• Git, GitHub, Docker

Projects

• Nurse Robot (Graduation Project with grade excellent)

  We built a nurse robot to help doctors in hospitals to avoid them from Corona Virus and we built a website and mobile application to control the robot We give it the number of room and name of patient and it goes to detect the QR code on rooms and when it detect the right room, it goes inside the right room and detect the patient by face recognition and gives him the medicine and take from him temperature and blood pressure and send the results to mobile application.

• Top 250 Movies in IMDB

  I scraped data from IMDB by using (python, beautiful soup) then I edited data by using power query on excel and made visualization by using power BI and finally made ML model to predict the No of Wins.

• English to Malay Translator

  Goal of that app translation from language to another, I used transformer model to build it, built decoder and encoder, English is encoder, and Malay is decoder made tokenizer by using BEP tokenizer.

• Credit Card Fraud Detection dataset:

  Goal of project is detected the fraud and nonfraud dataset on credit card transaction, I made visualize by using matplotlib and seaborn, add normalization by using standard scaler, add new features to improve the model, test many classification algorithms to know the best algorithm, evaluated model by using confusion matrix, classification report and Roc curve.

• Forecasting sales for 10 days (Time series data):

  Goal of model predict sales for 10 days starts from the day after the last day on dataset, I used XGBoosting because it gets relationship between inputs and target, I used suitable evaluate matric to evaluate the model and I made some Explore data analysis to get more insights

• Electric Vehicle Population Data:

  Goal of project analysis to get insights and build two model one to classify and the other for forecasting, I classified clean alternative fuel vehicle and I used logistics regression and made forecasting for vehicle’s population by using SARIMAX

Contact

email: youssefalzahar12@gmail.com

phone: +201271885939

kaggle: youssefelzahar

github: youssefelzahar