- π Technology in Data Science
- π‘ Passionate about solving real-world problems using Data Science, Machine Learning, and Data Engineering.
- π Currently exploring: Analytics, Business Intelligence, and Insight Generation β delivering value through data, actionable insights, impactful analyses, and compelling visualizations.
Data Science & Machine Learning:
- π EDA, Feature Engineering, Model Tuning (Python: Pandas, Scikit-learn, TensorFlow).
Data Engineering:
- π ETL/ELT pipelines, Data Warehousing (Airflow, Spark, dbt, Snowflake).
Visualization:
- π Dashboards and reports (Power BI, Tableau, Google Looker Studio).
- βοΈ Coming Soon: End-to-End Analytics Engineer Projects.
