[Book-2021] Practical MLOps O'Reilly Book

[📚💻] Notes, code examples and exercises based on the book Practical MLOps - Operationalizing Machine Learning Models by Noah Gift & Alfredo Deza

Notes and Exercises related to book : Practical MLOps By Noah Gift, Alfredo Deza

"Practical MLOps" Book Exercises, Tests and Practice solved by Enric Domingo while reading the book

The book's exerices and my notes

Practical MLOPS Book learning

Repo for reading book practical mlops

Chapter 4 of book Practical MLOps

Demos and notes from Practical MLOps book

Project gotten from the book: practical MLops

Inspired by the practical MLOPS book: https://learning.oreilly.com/library/view/practical-mlops/9781098103002/

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This repository will be used for deploy a personal ml model of mine.

Repository for following and implementing the content presented in the book “Practical MLOps - Operationalizing Machine Learning Models” by Noah Gift & Alfredo Deza.

Sandbox for the Practical MLOps book by O'Reilly

following along the book Practical MLOps from O`Reilly

Test the best practices of MLOPS from the Practical MLOps book by Noah

I start to learn MLOps and this is my journey to become MLOps engineer useing practical MLOps book

Practical implementation of codes provided in the book "Practical MLOPS - Operationalizing Machine Learning Models by O'Reilly".

Learnings from Noah Gift's Practical ML Ops book https://learning.oreilly.com/library/view/practical-mlops

Implementation repository for task in book "Machine Learning Engineering with Python: Manage the production life cycle of machine learning models using MLOps with practical examples"

This is a project scaffold as an answer to the first exercise of chapter 1 of the book entitled "Practical MLops" by Noah Gift & Alfredo Deza, O'Reilly, first edition, 2021

This project showcases a complete, end-to-end book recommender system, demonstrating the entire MLOps lifecycle. It covers data processing, model training, evaluation, and deployment. With a modular codebase and pipeline automation, this repository highlights practical skills in building and deploying production-ready ML applications.