🎓 Data & AI Engineer | Machine Learning Enthusiast | Software Developer

🚀 Passionate about AI, Data Science, and Software Engineering, I specialize in Machine Learning, NLP, CV, Deep Learning, and Backend Development. Whether it's developing ML-powered solutions, optimizing graph-based algorithms, or deploying scalable applications, I love solving complex problems with data-driven insights.

• 🎓 Currently: Master's student (Engineer's Degree, also known as Cycle d'Ingénieur in French) in my final year at ESILV, specializing in Data Science & AI.
• 🏢 Past Work: Experience in credit risk modeling, graph mining, and recommendation systems
• 🛠️ Tech Stack: Python, SQL, TensorFlow, PyTorch, Scikit-learn, Flask, FastAPI, Docker, CI/CD, Neo4j
• 📚 Projects: NLP-driven TripAdvisor Recommendation System, Real-time Chat Application, Graph-based School Donations Analysis, and more
• 🎯 Interests: AI for Cybersecurity, Finance, and Healthcare, Edge AI, and Scalable ML Systems

📌 Rating Prediction from Insurance Reviews (NLP Project)

• Objective: Predict insurer ratings from customer reviews and extract insights using NLP techniques
• Techniques Used: Text cleaning, TF-IDF, Word2Vec, LDA (Topic Modeling), Deep Learning, SHAP analysis
• Models: Logistic Regression, Random Forest, Neural Networks, RoBERTa, Llama 3.2 (LoRA fine-tuning)
• Deployment: Streamlit app for real-time rating predictions and explainability

📌 Machine Learning for Credit Risk Prediction

• Developed ML models for rating & default prediction of corporate issuers

📌 TripAdvisor Recommendation System (NLP)

• Implemented BM25 baseline & built an enhanced recommendation model
• Extracted semantic similarities from hotel reviews

📌 Real-time Chat App

• Built using Flask, Docker, CI/CD pipelines
• Achieved 20/20 at ESILV for architecture & performance

💡 Machine Learning & AI

• Supervised & Unsupervised Learning
• Explainable AI & Model Interpretability
• Deep Learning (CNNs, RNNs, Transformers)

💻 Development & Engineering

• Backend: Flask, FastAPI, Node.js
• Databases: SQL, MongoDB, Neo4j
• DevOps: Docker, CI/CD, GitHub Actions

📊 Data Science & Analytics

• Graph Mining & Network Analysis
• Natural Language Processing (NLP)
• Recommender Systems & Ranking Algorithms

🌐 Website/Portfolio: [Coming soon!]
💼 LinkedIn: linkedin.com/in/ahmedmaaloul
📧 Email: ahmed.maaloul@myyahoo.com

💡 Always open to collaborations, research, and new opportunities! 🚀