A growing collection of end-to-end data science projects, exploratory data analysis (EDA), and core Python problem-solving frameworks — built while training toward a Data Science / AI-ML career.
Automated data-quality checks and anomaly detection using statistical methods and Isolation Forest, served through an interactive Streamlit dashboard, with a synthetic data generator for testing at scale.
A grounded retrieval-augmented generation system — document ingestion, vector store and retrieval, grounded question-answering, and a Streamlit chat interface.
Object detection and action recognition pipelines built for video input, with a Colab workflow and smoke tests for reproducibility.
Exploratory data analysis notebooks (including a supermarket sales analysis), core Python/statistics practice, and a console-based smart calculator.
Python · Pandas · NumPy · Scikit-learn · Streamlit · SQL
Built by Ariea Sampat — Computer Engineering & MBA student at NMIMS MPSTME, building toward Data Science / AI-ML Engineering roles.