Summary

Machine learning engineer with experience in performing statistical analysis, exploring, preprocessing, visualizing the data and defining feature engineering and data augmentation pipelines. Proficient in Fine-tuning, developing, and implementing algorithms for Machine Learning, Deep Learning, and deploying the models to production to bring AI solutions to the market and make programs more effective.

Work Experience

Coding Raja Technologies

Machine Learning Intern

August 2023 - August 2023

  • I was involved in three tasks, the first task was to detect spam emails or messages using the Enron spam dataset.
  • The second task was to Recommend products to users based on their past behavior and preferences using the Amazon Product Reviews dataset.
  • The third task was to recognize handwritten digits or characters for the MNIST dataset.
  • Applied feature engineering, data preprocessing, and data augmentation, then trained and evaluated the model.

Paxera Health

Machine learning & Web development trainee

August 2022 - September 2022

  • Designed and developed a robust patient portal system utilizing the Asp.net MVC framework. Through my expertise, I successfully delivered a user-friendly and secure patient portal system that significantly enhanced the healthcare experience for users.
  • I was involved in tasks related to data preprocessing and feature engineering for cigarettes dataset, and deploying the model into a web interface for user interaction using Flask.
  • Communicated technical concepts to non-technical stakeholders through clear reports.

National Research Center

Machine learning & Bioinformatics trainee

July 2022 - August 2022

  • I deployed a pre-trained machine learning model on a breast cancer dataset provided by NRC enabling doctors to improve healthcare outcomes significantly.

Technical Skills

  • Main Skills

    Machine Learning

    Deep Learning

    Computer vision

    OpenCV

    Keras

    Tensorflow

    Scikit-Learn

    Pandas

    NumPy

    Data Analysis

    Data Modeling

    Statistics and Probability

    Mathematics

    Algorithms Analysis

    Data Structures

    Docker

    Linux

    Flask

    SQL

    Feature Engineering

    Data visualization

    Fine-tuning

  • Programming Skills

    Python

    C++

    C#

    R

    HTML

    CSS

    JavaScript

    PHP

  • Version Control

    Git

  • Cloud Platforms

    AWS

Education

Faculty of Computers and Artificial Intelligence, Cairo university

Bioinformatics department - Bachelor of Computer Science, GPA 3.44 (Very good)

2019 - 2023

Projects

Early detection of colon cancer – graduation project

  • Develop an early detection system for colon cancer using classification and segmentation techniques to identify and analyze suspicious regions of the colon which will help doctors in solving the high incidence and mortality rates of colon cancer, which is one of the most common types of cancer worldwide. Performed comprehensive data preprocessing and augmentation across diverse datasets, subsequently training and evaluated the models, then integrating this work into a user-friendly website using Flask framework.

Hepatocellular Carcinoma Analysis

  • This work was conducted using the dataset of HCC provided by doctors at Qasr Al-Eini. Statistical analysis and feature-feature correlation had been applied for the whole available data set using Pearson correlation and applied Feature-feature correlation for the whole available data set using Fisher correlation, then Applied dimensionality reduction using PCA. The data was trained on 5 Models, each model had been trained and evaluated before applying feature selection and PCA, then trained the best 2 models after applying the feature selection and PCA.

Mail-order Company's customers Analysis

  • Applied unsupervised learning techniques on demographic data for the general population of Germany and demographic data for customers of a mail-order company to organize the general population into clusters, then use those clusters to see which of them comprise the main user base for the company.

Donors prediction

  • Identify potential donors and reduce the overhead cost of sending mail, using various supervised learning techniques.