Hi, I'm Ahmed ElSany

Machine Learning Engineer || AI Enthusiast

About Me

Machine Learning Engineer with a strong background in Deep Learning, AI, and Computer Vision. Passionate about developing AI-driven solutions for real-world problems, with hands-on experience in building, training, and deploying ML models. Expertise in TensorFlow, PyTorch, and MLOps, with a focus on applications in healthcare, autonomous systems, and AI-powered software solutions.

Experience

AI Intern | Orange Digital Center Egypt

January 2025 – March 2025 | Hybrid

Participated in an intensive AI training program, focusing on advanced topics including Natural Language Processing (NLP), Computer Vision, GANs, VAEs, and MLOps. Designed and trained Machine Learning models using TensorFlow and Keras, and engaged in practical projects applying AI to real-world challenges.

Data Science & AI Lead | GDG On Campus Zagazig

September 2023 – Present | Zagazig

Leading data science projects, mentoring team members, and organizing workshops to enhance skills in AI, Machine Learning, and Data Analysis within a vibrant student community at Zagazig University.

Data Science & AI Intern | Microsoft Student Club – EELU

May 2024 – September 2024 | Remote

Worked on various machine learning projects, applying skills in data analysis, model development, and deployment. Responsibilities included developing and training ML models using Python (scikit-learn, Seaborn) and collaborating on ML solutions.

Artificial Intelligence Intern | Information Technology Institute (ITI)

August 2024 – September 2024 | Remote

Worked on ML projects involving data analysis, model development, and deployment. Gained hands-on experience in ML, Deep Learning, NLP, and developed a computer vision project. Responsibilities included designing and training models (TensorFlow, Keras) and collaborating on innovative AI solutions.

Skills

Machine Learning

Python
Numpy
Pandas
Data Cleaning
Data Preprocessing
Scikit-Learn
Hyperparameter Tuning
Model Selection
Feature Engineering
Model Evaluation

Deep Learning

PyTorch
TensorFlow / Keras
Computer Vision
Neural Networks
CNNs
RNNs
LSTMs
Transfer Learning
Object Detection
YOLO
OpenCV

Data Science

Linear Algebra
Probability and Statistics
Matplotlib
Seaborn
Data Visualization
Data Analysis

Deployment & MLOps

Flask
Docker
Model Deployment

Soft Skills

Problem-Solving & Critical Thinking
Teamwork & Collaboration
Creativity & Innovation
Time Management & Organization
Communication & Presentation
Continuous Learning

Projects

Deep Learning Projects

Rattel APP

An AI-powered application to recognize Quran reciters from live or audio recordings, identifying the Surah and Ayah number. (Available on App Store)

Technologies: Python, AI, Mobile Development

Download APP

Ocular Disease Classification

Developed a deep learning model to classify eye diseases from retinal images using Convolutional Neural Networks (CNNs).

Technologies: Python, Deep Learning, CNNs, Computer Vision

Project Link

Arabic Sentiment Analysis with NLP

Analyzes Arabic text to determine sentiment using NLP techniques. Helps in understanding public opinion and enhancing Arabic text analysis.

Technologies: Python, NLP, Arabic Text Processing, Machine Learning

Project Link

Traffic Sign Detection

Detecting traffic signs using computer vision and deep learning for autonomous vehicles.

Technologies: Python, Deep Learning, Computer Vision, CNNs

Project Link

YOLO-Based Car Detection

Improved YOLOv8 performance for car detection using transfer learning.

Technologies: Python, Deep Learning, YOLOv8, Transfer Learning, Computer Vision

Project Link

Potato Leaf Disease Prediction

Predicts potato leaf diseases using machine learning and image analysis.

Technologies: Python, Deep Learning, Image Processing

Project Link

Machine Learning Projects

Diameter Prediction of Asteroids

Predicts asteroid diameters using regression with NASA data. Achieves 97% accuracy.

Technologies: Python, Machine Learning, Regression, Data Analysis

Project Link

Neo-Hazard Prediction

Predicts natural hazards using ML techniques to anticipate risks and enhance preparedness.

Technologies: Python, Machine Learning, Data Analytics

Project Link

Credit Card Fraud Detection

Detects fraudulent transactions with 98% accuracy using ML classification.

Technologies: Python, Machine Learning, Data Preprocessing, Classification

Project Link

Mall Customers - K-means Clustering

Segments customers using K-means clustering to enhance marketing strategies.

Technologies: Python, K-means Clustering, Data Analytics

Project Link

House Prices Prediction

Predicts house prices using regression models with data visualization support.

Technologies: Python, Machine Learning, Regression, Data Visualization

Project Link

Publications

How to Get Started in AI?

Article on Medium

In this article, I discuss the fundamental concepts, essential tools, and learning resources for beginners looking to enter the world of Artificial Intelligence and Data Science.

Model Evaluation in Machine Learning: Classification Report and Metrics Guide

Article on Medium

In this article, I cover the key concepts and essential metrics for evaluating machine learning models. It’s a beginner-friendly guide to understanding accuracy, precision, recall, F1-score, and confusion matrices.