Pocket guide: The paths towards ML-ightenment

In this pocket guide, we offer a practical machine learning operations (MLOps) framework that captures the concepts and tools to accelerate a machine learning (ML) adoption journey.

What you'll learn This pocket guide has been written by Georgios Sakellariou, a Principal at Credera who has over 13 years of experience in delivering change to organisations across cloud and data, Adarsh Panda, who leads the UK Data Science Practice at Credera and has 20 years of experience in machine learning and artificial intelligence (ML & AI), and Harry Tsangari, a Consultant and the Operations Practice Lead at Credera who is passionate about advancements in the field of ML and AI. On downloading the guide, you will learn the basics of MLOps, why it has emerged in recent years, and how our MLOps framework can accelerate your ML adoption journey. Download the pocket guide and you'll gain insights into:

1. The underlying principles of MLOps.

2. Why MLOps has emerged in recent years.

3. The crucial link between MLOps and business strategy.

4. How an MLOps framework can benefit your organisation.

Who is it for? This pocket guide is relevant to business leaders such as CEOs, CDOs, CTOs, CIOs, and business decision makers with a technology, data, and machine learning agenda, as well as any data science and MLOps enthusiasts out there!