Resolving Data Sparsity in Recommender Systems Using Reinforcement Learning
Babol Noshirvani University of Technology
Data Analyst & ML practitioner with an M.Sc. in AI & Robotics, a B.Sc. in Industrial Engineering and a completed MBA. Core strengths: Python, SQL, NumPy, pandas and Git. I turn raw, messy data into structured pipelines, statistical analysis and dashboards that decision makers actually use.
Tehran, Iran · Data Science & AI
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I'm a data professional who enjoys the unglamorous parts as much as the modelling: cleaning, validation, tests and reproducibility. My work spans applied machine learning, NLP and business intelligence, always aimed at decision-ready insights for stakeholders.
I work mostly in Python (pandas, NumPy, scikit-learn, matplotlib) and the BI stack (Power BI, Power Query, DAX, star schemas), with SQL Server/T-SQL, Snowflake and Spark/Databricks for data engineering. I've also been building with LLMs, embeddings, agents and prompt engineering, and I care about data quality, lineage and governance as much as model scores.
Kharazmi University
Thesis: Addressing Data Sparsity in Recommender Systems via Reinforcement Learning
University of Tehran
Islamic Azad University
Adrin Darou Iranian · Karaj, Iran
MAPNA Turbine Engineering & Manufacturing Co. (TUGA) · Alborz Industrial City, Iran
Raw data → cleaning → analysis → models → dashboards.
Babol Noshirvani University of Technology