Practical full‑stack machine learning : A guide to build reliable, reusable, and production‑ready full‑stack ML solutions /

Kumar, Alok,

Practical full‑stack machine learning : A guide to build reliable, reusable, and production‑ready full‑stack ML solutions / Alok Kumar. - 1st edition. - 422 pages : illustrations ; 20 cm.

Includes bibliographical references.


1. Organizing Your Data Science Project ‡ 2. Preparing Your Data Structure ‡ 3. Building Your ML Architecture ‡ 4. Bye‑Bye Scheduler, Welcome Airflow ‡ 5. Organizing Your Data Science Project Structure ‡ 6. Feature Store for ML ‡ 7. Serving ML as API.


Practical guide introducing production‑ready full‑stack ML pipelines using Python. Covers feature engineering, dataops, Airflow, Dask, MLflow, SageMaker, FastAPI, and scalable API deployment.:contentReference[oaicite:1]


9789391030421


Machine learning--Implementation.
Python (Computer program language)--Programming.

006.3 / k.a.p.