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.

Deterministic decision gate for AI/ML systems. Risk-Gate enforces strict, schema-driven admissibility boundaries between AI/LLM intent and real system actions. It provides a fixed, human-owned decision structure with deterministic allow/block outcomes, explicit audit logging, and environment-specific policy via configuration — no ML, no heuristics,

Benchmarking and optimizing transformer inference across PyTorch, ONNXRuntime, and TensorRT with latency/throughput analysis on GPU and CPU.

A lightweight, reverse-mode Automatic Differentiation (AD) engine built from scratch using Python and NumPy. Supports dynamic computational graphs and complex linear algebra operations.

Public engineering notes (ML systems, CV, MIT courses). Notes-only; sources linked.

Introduction to Machine Learning Systems - Educational materials for ML systems architecture, deployment, and production considerations.

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.

An automated preprocessing pipeline for Telco Customer Churn data, including cleaning, feature engineering, and CI with GitHub Actions.

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.

Scalable Training Telemetry and Metrics Visualization