# graviraja/MLOps-Basics

Repository: https://github.com/graviraja/MLOps-Basics
Canonical: https://ross.abutalabs.com/products/mlops-basics
Language: Jupyter Notebook
License: MIT
License Family: permissive
Last push: 2024-09-22T19:19:29+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1949, "days_push": 710, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 8908, forks 1772 (observed 2026-08-28T04:10:26.238234+00:00)

## What it is
A week-by-week tutorial series (Jupyter notebooks plus blog posts) teaching MLOps fundamentals such as model building, experiment monitoring, configuration management, testing, packaging, deployment, and CI/CD. It uses tools like Hugging Face Transformers, PyTorch Lightning, Weights & Biases, and Hydra.

## Use cases
- learn mlops basics from scratch
- how to track machine learning experiments with weights and biases
- manage ml project configurations with hydra
- deploy machine learning models and set up cicd
- structure a pytorch lightning training project
- monitor model performance in production

## When to choose
- you are new to MLOps and want a guided, hands-on curriculum
- you want practical examples combining PyTorch Lightning, W&B, and Hydra
- you prefer learning through notebooks and accompanying blog posts

## When to avoid
- you need production-grade, maintained MLOps tooling rather than educational material
- you want advanced or enterprise MLOps topics beyond the basics
- you need a supported software product with guarantees

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, monitoring, ci-cd, configuration-management, deployment, testing
- domain: machine-learning, tutorials, deep-learning
- platform: python, cross-platform
- tags: mlops, tutorial-series, pytorch-lightning, weights-and-biases, hydra, cicd, model-deployment, jupyter-notebooks, devops

## Member repositories
- graviraja/MLOps-Basics (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:26.238234+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:24:43.210891+00:00, confidence not recorded.
  - readme: https://github.com/graviraja/MLOps-Basics (fetched 2026-08-28T04:10:26.238234+00:00, sha 11c9275eb342)
- Data as of 2026-08-30T08:39:29.467469+00:00.