Data Engineering for Multimodal AI by Vasundra Srinivasan (.ePUB)
File Size: 23 MB
Data Engineering for Multimodal AI: Architecting Scalable Systems for Next-Generation AI Applications by Vasundra Srinivasan
Requirements: .ePUB reader, 23 mb
Overview: AI is only as capable as the context it’s given, and context is a data engineering problem before it’s a model problem. As multimodal AI systems and applications become increasingly sophisticated and data-hungry, the infrastructure that produces and governs that context has to evolve to keep pace.
Data Engineering for Multimodal AI is one of the first practical guides for data engineers, machine learning engineers, and MLOps specialists looking to rapidly master the skills needed to build robust, scalable data infrastructures that multimodal AI systems and applications depend on for effective context engineering. You’ll follow the entire lifecycle of AI-driven data engineering, from conceptualizing data architectures to implementing data pipelines optimized for multimodal learning in both cloud-native and on-premises environments. And each chapter includes step-by-step guides and best practices for implementing key concepts.
Genre: Non-Fiction > Tech & Devices
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