Two weeks in, you have all the pieces: Git and DVC for versioning, MLflow for tracking, and Docker for reproducible environments. A single docker compose up that spins up a tracking server, runs a versioned experiment, and logs every result. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 14)
Stop running MLflow and your training script in separate terminals. Today you'll wire them together with Docker Compose , one command, a full local ML platform, ready to log every experiment automatically. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 13)
AI-powered conversational document assistant with RAG, Qdrant & a complete MLOps pipeline using Docker Compose
A Practical Guide to Deploying Secure, Scalable, and Password-Free Authentication for Modern Applications
A Hands-on Guide for Cloud & DevOps Engineers to Build and Deploy an Automated Content Scheduling and Social Media Posting System
Building a Lightweight OAuth 2.0 Provider with Node.js, Express & MongoDB. Run & test locally using Docker Compose & deploy to AWS Lambda
Example: Kubernetes, Terraform, Docker, AWS, MLOps...
