🎓 I'm a final-year Software Engineering student passionate about AI technologies and automation.
🔍 My main areas of interest include semantic search, recommendation systems, and vector databases.
⚡ I have practical experience with Qdrant and Superlinked, which I’ve used to build scalable and efficient search and recommendation systems.
🐍💡 I have hands-on experience in Python and Go, and I’ve also been working extensively with Robotic Process Automation (RPA), particularly UiPath.
🚀 I enjoy creating intelligent and efficient solutions that address real-world problems.
- İstanbul/Turkiye
- in/gururaser
- https://medium.com/@gururaser
Highlights
- Pro
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qdrant-score-boosting-ecommerce
qdrant-score-boosting-ecommerce PublicHow Qdrant's Score Boosting feature can personalize e-commerce search results without training data, complex pipelines, or Learning-to-Rank models.
Jupyter Notebook 5
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qdrant-intent-aware-hybrid-search
qdrant-intent-aware-hybrid-search PublicIntent-aware hybrid search for e-commerce using Qdrant, IBM Granite embeddings, and Gemini 3.1 Flash Lite.
Jupyter Notebook 4
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gemini-batch-embedding-pipeline
gemini-batch-embedding-pipeline PublicETL pipeline that generates embeddings for any HuggingFace dataset using the Gemini Embedding 2 model via the Gemini Batch API, then stores them in Qdrant for vector search. Supports text, image, a…
Python
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film-analysis-project
film-analysis-project PublicExploratory Data Analysis and Visualization of Films from 1980-2020
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karar
karar PublicKarar, BTK Hackathon 2026 için özel olarak geliştirilmiş yapay zekâ tabanlı bir arama (Agentic Search) projesidir.
TypeScript
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