The machine learning solutions architect handbook /
Ping, David
The machine learning solutions architect handbook / David Ping - 2nd ed. - Birmingham : Packt Publishing, 2024 - xxii, 569 p.
Index present
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 eBook Key Features Solve large-scale ML challenges in the cloud with several open-source and AWS tools and frameworks Apply risk management techniques in the ML life cycle and learn architecture patterns for solutions Understand the challenges and risks of implementing generative AI 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. 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.
Eng
9781805122500
Machine learning
Computer architecture
System design
006.31 / PIN-M
The machine learning solutions architect handbook / David Ping - 2nd ed. - Birmingham : Packt Publishing, 2024 - xxii, 569 p.
Index present
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 eBook Key Features Solve large-scale ML challenges in the cloud with several open-source and AWS tools and frameworks Apply risk management techniques in the ML life cycle and learn architecture patterns for solutions Understand the challenges and risks of implementing generative AI 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. 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.
Eng
9781805122500
Machine learning
Computer architecture
System design
006.31 / PIN-M