AI Agents Course
A Practical Deep Dive Into Memory Optimization for Agentic Systems (Part B)
AI Agents Crash Course—Part 16 (with implementation).
Avi Chawla
410 posts published
MLOps/LLMOps Course
Foundations of AI Engineering and LLMs
LLMOps Part 1: An overview of AI engineering and LLMOps, and the core dimensions that define modern AI systems.
LLM and Fine-tuning
A Practical Guide to Integrate Evaluation and Observability into LLM Apps
A comprehensive guide to Opik, an open-source LLM evaluation and observability framework.
MLOps/LLMOps Course
CI/CD Workflows
MLOps Part 18: A hands-on guide to CI/CD in MLOps with DVC, Docker, GitHub Actions, and GitOps-based Kubernetes delivery on Amazon EKS.
MLOps/LLMOps Course
Monitoring and Observability: Practical Tooling with Evidently, Prometheus, and Grafana
MLOps Part 17: ML monitoring in practice with Evidently, Prometheus and Grafana, stitched into a FastAPI inference service with drift reports, metrics scraping, and dashboards.
AI Agents Course
A Practical Deep Dive Into Memory Optimization for Agentic Systems (Part A)
AI Agents Crash Course—Part 15 (with implementation).
LLMs
Verbalized Sampling in LLMs
...explained with usage.
MLOps/LLMOps Course
Monitoring and Observability: Core Fundamentals
MLOps Part 16: A comprehensive overview of drift detection using statistical techniques, and how logging and observability keep ML systems healthy.
MLOps/LLMOps Course
Model Deployment: EKS Lifecycle and Model Serving
MLOps Part 15: Understanding the EKS lifecycle, getting hands-on with AWS setup, and deploying a simple ML inference service on Amazon EKS.
MLOps/LLMOps Course
Model Deployment: Introduction to AWS
MLOps Part 14: Understanding AWS cloud platform, and zooming into EKS.
MCP Guidebook
Build an MCP-powered Audio Analysis Toolkit
...explained step-by-step with code.
MCP Guidebook
Build an MCP-powered RAG over Videos
Chat with videos and get precise timestamps.
LLMs
ARQ: A New Structured Reasoning Approach for LLMs
...that actually prevents hallucinations (explained visually).
MLOps/LLMOps Course
Model Deployment: Cloud Fundamentals
MLOps Part 13: An overview of cloud concepts that matter, from virtualization and storage choices to VPC, load balancing, identity, and observability.
MLOps/LLMOps Course
Model Deployment: Kubernetes
MLOps Part 12: An introduction to Kubernetes, plus a practical walkthrough of deploying a simple FastAPI inference service using Kubernetes.
MCP Guidebook
MCP-powered Deep Researcher
Multi-agent (100% local).
MCP Guidebook
MCP-powered Synthetic Data Generator
Generate realistic data using existing data (100% local).
MCP Guidebook
MCP-powered RAG Over Complex Docs
...with hands-on implementation.
MLOps/LLMOps Course
Model Deployment: Serialization, Containerization and API for Inference
MLOps Part 11: A practical guide to taking models beyond notebooks, exploring serialization formats, containerization, and serving predictions using REST and gRPC.
LLMs
Build and Deploy Agents to Production
...explained step-by-step.
MCP Guidebook
Build a Shared Memory for Claude Desktop and Cursor
100% local.
MCP Guidebook
Build an MCP Server to Connect to 200+ Data Sources
A unified MCP server for all your data (100% local).
MCP Guidebook
An MCP-powered Voice Agent
...powered by Qwen 3 LLM.
MLOps/LLMOps Course
Model Development and Optimization: Compression and Portability
MLOps Part 10: A comprehensive guide to model compression covering knowledge distillation, low-rank factorization, and quantization, followed by ONNX and ONNX Runtime as the bridge from training frameworks to fast, portable production inference.
MLOps/LLMOps Course
Model Development and Optimization: Fine-Tuning, Pruning, and Efficiency
MLOps Part 9: A deep dive into model fine-tuning and compression, specifically pruning and related improvements.
