Supercharge Your Model Training
Designing IT and ML Applications using Systems Thinking Approach at IIT Bhilai (CS559)
Structured notes on designing scalable and fault-tolerant ML systems, to refresh your knowledge and help you prepare for a system design interview. Covers system design, MLOps, and case studies.
A lightweight, reverse-mode Automatic Differentiation (AD) engine built from scratch using Python and NumPy. Supports dynamic computational graphs and complex linear algebra operations.
Production-style ML inference system for Pneumonia detection from chest X-rays, featuring custom CNN architectures, versioned model serving, preprocessing parity, observability, drift detection, and rollback using FastAPI and Docker.
End-to-end personalized feed ranking system demonstrating retrieval → ranking pipelines, offline evaluation, realistic simulation, and business-aligned diagnostics inspired by large-scale social platforms.
Introduction to Machine Learning Systems - Educational materials for ML systems architecture, deployment, and production considerations.
An automated preprocessing pipeline for Telco Customer Churn data, including cleaning, feature engineering, and CI with GitHub Actions.
Scalable Training Telemetry and Metrics Visualization
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