Hi, I'm Rachit 👋

I’m building end-to-end machine learning systems, focusing on turning data into actionable insights through structured pipelines and models.

Currently, I’m working on CartIQ, an ML-based system for:

• Customer segmentation (clustering)
• Churn prediction (classification)
• Spend prediction (regression)
• Recommendation systems (hybrid)

• Designing clean ML pipelines (train → predict → evaluate)
• Building backend systems using FastAPI
• Strengthening DSA for problem-solving and system thinking
• Exploring AI engineering concepts (model integration, workflows)

• Moving beyond notebooks → building complete ML systems
• Learning deployment & MLOps fundamentals
• Applying DSA concepts where relevant (optimization, efficiency)

Machine Learning • AI Engineering • Backend Systems • Data Engineering • Recommendation Systems • Scalable ML Systems

🛒 CartIQ — E-commerce Intelligence System
Customer segmentation (clustering)
Churn prediction (classification)
Spend prediction (regression)
Recommendation system (hybrid)

Pandas, NumPy, Scikit-learn
FastAPI (planned)
Streamlit Modular ML pipelines
Matplotlib

Build real systems. Not just notebooks.
Consistency > Motivation