David Ping

The Machine Learning Solutions Architect Handbook (eBook, ePUB)

Practical strategies and best practices on the ML lifecycle, system design, MLOps, and generative AI

• Format: ePub

Produktbeschreibung

David Ping, Head of GenAI and ML Solution Architecture for global industries at AWS, provides expert insights and practical examples to help you become a proficient ML solutions architect, linking technical architecture to business-related skills.
You'll learn about ML algorithms, cloud infrastructure, system design, MLOps , and how to apply ML to solve real-world business problems. David explains the generative AI project lifecycle and examines Retrieval Augmented Generation (RAG), an effective architecture pattern for generative AI applications. You'll also learn about open-source technologies, such as Kubernetes/Kubeflow, for building a data science environment and ML pipelines before building an enterprise ML architecture using AWS. As well as ML risk management and the different stages of AI/ML adoption, the biggest new addition to the handbook is the deep exploration of generative AI.
By the end of this book , you'll have gained a comprehensive understanding of AI/ML across all key aspects, including business use cases, data science, real-world solution architecture, risk management, and governance. You'll possess the skills to design and construct ML solutions that effectively cater to common use cases and follow established ML architecture patterns, enabling you to excel as a true professional in the field.

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Produktdetails

• Verlag: Packt Publishing
• Seitenzahl: 602
• Erscheinungstermin: 15. April 2024
• Englisch
• ISBN-13: 9781805124825
• Artikelnr.: 70400013

Autorenporträt

David Ping is an accomplished author and industry expert with over 28 years of experience in the field of data science and technology. He currently serves as the leader of a team of highly skilled data scientists and AI/ML solutions architects at AWS. In this role, he assists organizations worldwide in designing and implementing impactful AI/ML solutions to drive business success. David's extensive expertise spans a range of technical domains, including data science, ML solution and platform design, data management, AI risk, and AI governance. Prior to joining AWS, David held positions in renowned organizations such as JPMorgan, Credit Suisse, and Intel Corporation, where he contributed to the advancements of science and technology through engineering and leadership roles. With his wealth of experience and diverse skill set, David brings a unique perspective and invaluable insights to the field of AI/ML.