Retail Sales Insight
Retail sales analysis using Python, Pandas, NumPy, SQLite, Matplotlib and Seaborn to clean data, explore trends and generate business insights.
A focused collection of work across data analytics, data science, machine learning, applied AI, and backend engineering. Analytics and ML projects come first.
Retail sales analysis using Python, Pandas, NumPy, SQLite, Matplotlib and Seaborn to clean data, explore trends and generate business insights.
End-to-end workflow for extracting sales data, transforming records, handling quality issues, engineering features and preparing data for analysis.
Salary prediction project using employee attributes and machine learning, supported by model evaluation and business-oriented Power BI reporting.
Applied customer analytics combining churn prediction, KMeans segmentation, NLP sentiment analysis, interactive Streamlit reporting and recommendations.
Visualization project focused on sales trends, product performance, regional distribution and statistical patterns using Python plotting tools.
Machine learning classification service exposed through FastAPI with preprocessing, engineered features, Random Forest modeling and validation.
AI-powered document processing application that extracts structured candidate information from resumes and stores normalized results through an API.
Retrieval-Augmented Generation application with document ingestion, semantic retrieval, conversational memory, vector storage and booking workflow.
REST API for patient records with CRUD operations, Pydantic validation, JSON persistence, BMI calculation and health classification.