Docker for ML Engineers
Containerize your ML code so it runs identically everywhere — on your laptop, on a teammate's machine, and in production — with zero "works on my machine" surprises. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 11)
100 Days of MLOps23
This roadmap takes you from zero MLOps knowledge to a production-ready ML engineer capable of building, deploying, monitoring, and automating end-to-end machine learning pipelines. You will master tools like MLflow, Docker, Kubernetes, Kubeflow, and cloud ML platforms while applying best practices in CI/CD, model governance, and observability. By Day 100, you will be able to design and operate scalable, reliable ML and LLM systems in real-world environments.
Check out the latest posts
Hyperparameter Tuning & Experiment Comparison
Systematic search strategies, MLflow-tracked runs, and the art of comparing hundreds of experiments to extract your best-performing model. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 10)
MLflow Projects & Model Registry
Stop running ML code in isolation. MLflow Projects make your experiments reproducible on any machine — while the Model Registry gives your models a professional lifecycle: from experiment to staging to production. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 9)
Experiment Tracking with MLflow
Stop losing track of your best model. Learn how MLflow turns chaotic trial-and-error into a reproducible, queryable history of every experiment you've ever run. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 8)
Review Week 1 & Build a Simple ML Project
Consolidate everything from Days 1–6 by building a fully versioned, end-to-end Iris classification project with Git, DVC, and a reproducible pipeline. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 7)
DVC Pipelines & Experiment Tracking
Stop running scripts manually. Learn how to define reproducible, dependency-aware ML pipelines using DVC's declarative dvc.yaml, track every run automatically, and share exact pipeline states with your team — no Makefile required. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 6)