Machine Learning • Deep Learning • Neural Networks • Artificial Intelligence • Data Mining • Predictive Analytics • Statistical Modeling • Algorithm Design • Feature Engineering • Model Optimization •

Natural Language Processing • Computer Vision • Big Data • Data Visualization • Python • TensorFlow • PyTorch • Scikit-learn • Pandas • NumPy • Jupyter • Apache Spark •

Classification • Regression • Clustering • Dimensionality Reduction • Time Series Analysis • Reinforcement Learning • Ensemble Methods • Cross Validation • Hyperparameter Tuning •

Data Engineering • ETL Pipelines • SQL • NoSQL • Cloud Computing • AWS • Docker • Git • API Development • Web Scraping • Data Warehousing • Business Intelligence •

Hassan Zoghly

Data Scientist & AI Engineer

Transforming raw data into intelligent solutions through Machine Learning, Deep Learning, NLP, and Computer Vision. I build AI systems that solve real-world problems.

About Me

Who I Am

I'm Hassan Zoghly, a passionate Data Scientist and AI Engineer currently pursuing my Bachelor's degree in Artificial Intelligence and Data Science at Menoufia University, Egypt. My academic journey has equipped me with both theoretical foundations and practical expertise in cutting-edge AI technologies.

My Expertise

My technical expertise spans across multiple domains of artificial intelligence:

Machine Learning: Building predictive models and statistical algorithms
Deep Learning: Designing neural networks using PyTorch and TensorFlow
Natural Language Processing: Developing text analysis and language understanding systems
Computer Vision: Creating image recognition and visual analysis solutions
Data Engineering: Building robust data pipelines and processing systems

What Drives Me

I'm passionate about bridging the gap between complex AI theory and practical, real-world applications. Every project I undertake is driven by the question: 'How can this technology make a meaningful difference?' Whether it's developing systems for traffic safety, creating tools for better communication, or uncovering insights from massive datasets, I focus on solutions that create tangible value.

My Approach

I believe in the power of data-driven decision making and evidence-based solutions. My approach combines rigorous technical implementation with creative problem-solving, ensuring that every AI system I build is not only technically sound but also user-focused and ethically responsible.

Download My CV

Education

BS in AI & Data Science

University

Menoufia University, Egypt

GPA

3.4

Location

El Mansoura, Ad Daqahliyah, Egypt

Phone

+20 102 983 0121

hassanzogly@gmail.com

Services & Solutions

Machine Learning Solutions

Custom predictive models for business forecasting
Classification and regression algorithms
Model optimization and performance tuning
Statistical analysis and data modeling

Deep Learning Development

Neural network architecture design
Computer vision applications
Natural language processing systems
Reinforcement learning agents

Data Analysis & Visualization

Exploratory data analysis (EDA)
Interactive dashboard creation
Statistical reporting and insights
Data storytelling and presentation

Data Engineering & Pipeline Development

Web scraping and data collection
ETL pipeline development
Data cleaning and preprocessing
Database design and optimization

AI Consulting & Strategy

AI solution architecture planning
Technology stack recommendations
Project feasibility analysis
Implementation roadmap development

Custom Software Development

Python application development
Streamlit web application creation
API development and integration
Automation tool development

Technical Skills

Python

Statistics

Machine Learning

Deep Learning

PyTorch

Computer Vision

NLP

Time Series

Power BI

Excel

SQL

Big Data

Linux

Web Scraping

Streamlit

Work Experience

Coming Soon...

Stay tuned for exciting updates about my professional journey.

My Projects

Sports Popularity Analysis with Web Scraping

May 2025

Conducted comprehensive analysis of global sports popularity trends by developing an automated data collection system that scraped information from Google Trends and YouTube analytics. Built a robust data pipeline handling large-scale web scraping while respecting rate limits and API constraints.

Key Achievements:

• Successfully processed over 10,000+ data points across 50+ sports categories
• Identified seasonal trends in sports viewership
• Created predictive models for future popularity spikes
• Applied statistical analysis for correlation patterns

Tools:

Python BeautifulSoup pandas matplotlib Google Trends API

View on GitHub

DQN Agent for 2048 Game (Reinforcement Learning)

May 2025

Designed and implemented a Deep Q-Learning agent capable of learning optimal strategies for the 2048 puzzle game through reinforcement learning. Demonstrates advanced understanding of neural network architectures and reward-based learning systems.

Key Achievements:

• Achieved average scores of 15,000+ points
• Successfully reached 2048 tile in 85% of games
• Demonstrated clear learning progression over 10,000+ training episodes
• Implemented sophisticated reward shaping strategies

Tools:

Python PyTorch NumPy Matplotlib Reinforcement Learning

View on GitHub

Auto-Correct System using NLP & Edit Distance

May 2025

Developed a sophisticated spelling correction system that mimics Google's "Did you mean...?" functionality using advanced NLP techniques and probabilistic models. The system combines multiple correction strategies to provide highly accurate suggestions.

Key Achievements:

• Achieved 92% accuracy on standard spelling correction benchmarks
• Handled over 50,000+ vocabulary words
• Successfully corrected complex multi-word errors
• Built probabilistic language models using trigram analysis

Tools:

Python NLTK spaCy Edit Distance N-gram models

View on GitHub

Traffic Sign Detection and Classification (GTSRB)

December 2023

Developed a robust convolutional neural network for real-time traffic sign detection and classification using the German Traffic Sign Recognition Benchmark (GTSRB) dataset. The system is designed for potential integration into autonomous vehicle perception systems.

Key Achievements:

• Achieved 98.5% classification accuracy on test set
• Reduced inference time to <50ms per image
• Successfully handled various lighting and weather conditions
• Designed custom CNN architecture with 43 different classes

Tools:

Python TensorFlow Keras OpenCV Computer Vision

View on GitHub

Hassan Zoghly

Data Scientist & AI Engineer

About Me

Who I Am

My Expertise

What Drives Me

My Approach

Services & Solutions

Machine Learning Solutions

Deep Learning Development

Data Analysis & Visualization

Data Engineering & Pipeline Development

AI Consulting & Strategy

Custom Software Development

Technical Skills

Work Experience

My Projects

Sports Analysis

2048 DQN Agent

Auto-Correct System

Traffic Sign Detection

Sports Popularity Analysis with Web Scraping

Key Achievements:

Tools:

DQN Agent for 2048 Game (Reinforcement Learning)

Key Achievements:

Tools:

Auto-Correct System using NLP & Edit Distance

Key Achievements:

Tools:

Traffic Sign Detection and Classification (GTSRB)

Key Achievements:

Tools:

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