DataTalks.Club

Engineering MLOps

by Emmanuel Raj

The book of the week from 05 Jul 2021 to 09 Jul 2021

MLOps is a systematic approach to building, deploying, and monitoring machine learning (ML) solutions. It is an engineering discipline that can be applied to various industries and use cases. This book presents comprehensive insights into MLOps coupled with real-world examples to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production.

The book begins by familiarizing you with the MLOps workflow so you can start writing programs to train ML models. Then you’ll then move on to explore options for serializing and packaging ML models post-training to deploy them to facilitate machine learning inference, model interoperability, and end-to-end model traceability. You’ll understand how to build ML pipelines, continuous integration and continuous delivery (CI/CD) pipelines, and monitoring pipelines to systematically build, deploy, monitor, and govern ML solutions for businesses and industries. Finally, you’ll apply the knowledge you’ve gained to build real-world projects.

By the end of this ML book, you’ll have a 360-degree view of MLOps and be ready to implement MLOps in your organization.

To take part in the book of the week event:

  • Register in our Slack
  • Join the #book-of-the-week channel
  • Ask as many questions as you'd like
  • The book authors answer questions from Monday till Thursday
  • On Friday, the authors decide who wins free copies of their book

To see other books, check the the book of the week page.

Subscribe to our weekly newsletter and join our Slack.
We'll keep you informed about our events, articles, courses, and everything else happening in the Club.


DataTalks.Club Hosted on GitHub Pages