Full archive
This archive is structured to grow over time. It includes Applied AI, Data Science, automation work, market intelligence, engineering projects, retail learning, and MBA case notes, with each item framed by the decision it supports.
Image-led search flow that reduced discovery friction when users did not know the exact product name.
Learning
Applied AI becomes valuable when it removes effort at a specific point in the purchase journey.
Hourly anomaly detection that surfaced order drops early enough for faster operational follow-up.
Learning
Data Science work matters most when it connects signals to urgency and clear follow-up decisions.
RAG workflow for searching PDFs and internal documents without repeated manual lookup.
Learning
Retrieval work is useful when it makes internal knowledge easier to reach at the moment of need.
OCR and parsing workflow for extracting invoice and PDF data from repeated operational tasks.
Learning
Practical automation becomes valuable when it removes repeated operational friction.
Price crawling, fuzzy matching, and dashboards for tracking competitor movement across 9 sites.
Learning
Pricing is not only a technical tracking problem; it is a business signal.
Real-time order-status scraping connected to more timely customer notification workflows.
Learning
Customer communication improves when operational visibility improves.
Automated content collection workflow for improving publishing consistency and audience relevance.
Learning
Content operations need both relevance and reliable cadence.
LLM and image-processing work aimed at improving the reliability of a crop advisory workflow.
Learning
AI in agriculture needs reliability, context, and practical usefulness.
Prediction model for identifying likely order cancellations earlier in the confirmation workflow.
Learning
Predictive work matters when it improves workflow timing and reduces uncertainty.
Production Python reliability and runtime improvements with alerts and database refinements.
Learning
Performance is not just engineering polish; it changes operational reliability.
Real-time collaborative diagram platform with document sharing.
Learning
Early experience in real-time collaboration, authentication, and full-stack architecture.
Stock price prediction app with forecasting and interactive visualizations.
Learning
Forecasting becomes useful only when the output is interpretable.
Deep learning ensemble model for leather defect detection with Flask integration.
Learning
Model accuracy depends heavily on environment, data quality, and deployment context.
A small learning note on customer education, trust, category understanding, and local retail behavior.
Learning
Retail taught me how trust, aspiration, pricing, and education influence customer decisions.
A future space for product, marketing, strategy, consumer behavior, and market analysis work.
Learning
This section should grow from real coursework, cases, observations, and projects rather than filler content.