The Machine Learning Solutions Architect Handbook: Practical strategies and best practices on the ML lifecycle, system design, MLOps, and generative AI

Design, build, and secure scalable machine learning (ML) systems to solve real-world business problems with Python and AWS

Key Features

• Go in-depth into the ML lifecycle, from ideation and data management to deployment and scaling
• Apply risk management techniques in the ML lifecycle and design architectural patterns for various ML platforms and solutions
• Understand the generative AI lifecycle, its core technologies, and implementation risks

Book Description

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.