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

The Machine Learning Solutions Architect Handbook

<span xml:lang="en">The Machine Learning Solutions Architect Handbook: Practical strategies and best practices on the ML lifecycle, system design, MLOps, and generative AI</span>

Ping, David

Design, build, and secure scalable machine learning (ML) systems to solve real-world business problems with Python and AWS Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesGo in-depth into the ML lifecycle, from ideation and data management to deployment and scalingApply risk management techniques in the ML lifecycle and design architectural patterns for various ML platforms and solutionsUnderstand the generative AI lifecycle, its core technologies, and implementation risksBook DescriptionDavid Ping, Head of GenAI and ML Solution Architecture for global industries at...

Design, build, and secure scalable machine learning (ML) systems to solve real-world business problems with Python and AWS Purchase of the print or...

Format

The Machine Learning Solutions Architect Handbook

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

David Ping

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