AI and Data Portfolio

MOHAMMED DARRIGE

⚡ Deep Learning Intern (July 13 – August 11, 2026)

3rd-year Artificial Intelligence and Data Engineering student at Fırat University. Focused on architecting production-ready AI systems, automated NLP pipelines, and practical tools that make complex models truly usable.

Mohammed Darrige markMohammed Darrige mark

Location

Fırat University, Turkey

Tech Stack

Python, Scikit-learn, PyTorch, TensorFlow, FastAPI, NLP, Image Processing

Currently Learning

RAG, NLP, image processing, and practical AI products

Profile

About

Specializing in transforming cutting-edge deep learning models into practical, automated software systems. Focused on building usable, production-ready NLP and RAG pipelines that solve real-world problems.

ML/DL Foundation

Solid grounding in core machine learning and deep learning architectures. Emphasizing rigorous experimentation, robust model evaluation, and high-performance inference pipelines.

Current Areas

Engineering end-to-end AI workflows that transform isolated experiments into fully automated, usable software systems. Focus areas include advanced NLP, computer vision, and scalable RAG architectures.

Engineering Philosophy

Static notebooks don't ship. I build end-to-end AI systems—from training and fine-tuning to deploying clean API endpoints and functional UIs that deliver real user value.

Work

Selected Projects

3 projects

Generative Image AI

Neural Style Studio: Custom SD 1.5 LoRA Engine

Applies the selected art movement to uploaded images using lightweight LoRA adapters trained for Cubism, Post-Impressionism, and Ukiyo-e.

PythonPyTorchDiffusersLoRAFastAPI

Probabilistic Deduction Engine

Neural Akinator: Dynamic Constraint & Decision Engine

A noise-tolerant Bayesian deduction engine that selects atomic questions through expected information gain across a curated 115-animal knowledge base.

Next.jsTypeScriptBayesian InferenceShannon EntropyInformation Gain

Natural Language Processing & RAG Systems

Enterprise-Grade Turkish NLU + RAG Pipeline

Production-ready system featuring two-stage intent classification and ChromaDB vector routing for high-accuracy Turkish customer NLU.

Turkish NLPIntent ClassificationRAGChromaDB
In Progress
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Let’s Talk

Contact

Open to internships and collaborations in AI engineering, applied machine learning, and projects that can become real products.