At FlyRank AI, I’m developing a content-refresh and opportunity-scoring model that ranks web pages by predicted organic-growth potential using a proprietary search-performance dataset. I’m working through the ML lifecycle, from exploratory analysis and feature engineering to evaluation and interpretability, in a review-gated workflow.
At EDXcellence LLP, I designed and developed a supervised-learning model for customer churn prediction. I prepared and engineered the data, benchmarked classification algorithms, and created visualizations and reports to support business insights.
On my AI Log Classification & Intelligence System project, I combined rules, transformer-based classification, and a Groq LLM, then exposed the pipeline through a FastAPI endpoint and Streamlit dashboard. I also built a cold-mail generator using LangChain and ChromaDB to create role-specific outreach and retrieve relevant portfolio projects.
