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Focused on semantic search
🎯
Focused on semantic search

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gururaser/README.md

Hi, I'm Gurur 🌟 Welcome to my GitHub page 💻

🎓 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.

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  1. RoleRadar RoleRadar Public

    RoleRadar turns free-form requests like “Data Analyst roles in New York with SQL experience.” into structured filters and semantic-vector queries, delivering spot-on matches in seconds.

    Jupyter Notebook 6

  2. karar karar Public

    Karar, BTK Hackathon 2026 için özel olarak geliştirilmiş yapay zekâ tabanlı bir arama (Agentic Search) projesidir.

    TypeScript 1

  3. qdrant-score-boosting-ecommerce qdrant-score-boosting-ecommerce Public

    How Qdrant's Score Boosting feature can personalize e-commerce search results without training data, complex pipelines, or Learning-to-Rank models.

    Jupyter Notebook 5

  4. qdrant-intent-aware-hybrid-search qdrant-intent-aware-hybrid-search Public

    Intent-aware hybrid search for e-commerce using Qdrant, IBM Granite embeddings, and Gemini 3.1 Flash Lite.

    Jupyter Notebook 4

  5. gemini-batch-embedding-pipeline gemini-batch-embedding-pipeline Public

    ETL 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

  6. film-analysis-project film-analysis-project Public

    Exploratory Data Analysis and Visualization of Films from 1980-2020

    Jupyter Notebook 3 2