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 in Credera’s UK offices who has over 13 years of experience in delivering change to organizations across cloud and data, Adarsh Panda, who leads Credera’s UK data science practice and has 20 years of experience in machine learning and artificial intelligence (ML and 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. When you download the guide, you will learn the basics of MLOps, why it has emerged in recent years, and how Credera’s MLOps framework can accelerate your ML adoption journey. Download the pocket guide and you'll gain insights into:
The underlying principles of MLOps.
Why MLOps has emerged in recent years.
The crucial link between MLOps and business strategy.
How an MLOps framework can benefit your organization.
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!
- Artificial Intelligence
- Data Science, Artificial Intelligence & Machine Learning
- Machine Learning Applications
- Machine Learning
The path towards ML-ightenment
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