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Architecting Data And Machine Learning Platforms By Lakshmanan - Paperback

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size

22.86 x 17.78 x 1.02 cm

Product Information

Brand Name

Books Kingdom

Ideal For

General Readers, Fiction Lovers, Mythology & Historical Fiction Readers, Indian Mythology Enthusiasts, Young Adults (YA) & Adults, College Students, Competitive Exam Aspirants (General Reading / Culture), Gift Purpose (Books Gift Set), Spiritual & Philosophy Interest Readers, Library / Book Collection Buyers

Material

Paperback

Country Of Origin

India

Pack Of

1

About Author

Dr. Valliappa ("Lak") Lakshmanan Is Co-Founder And Cto Of Obin Ai, A Startup That'S Building Deep Domain Ai Agents For Finance. He Sets The Technology And Science Direction Of The Company And Is Responsible For Building The Product.

Author Name

Valliappa Lakshmanan

Genre

Computer Science

No Of Pages

364

Publisher

Books Kingdom

Product Description


  • Premium Quality: Architecting Data and Machine Learning Platforms is a 364-page paperback handbook written for cloud architects who need to design, build, and modernise cloud-native data and machine learning platforms.

  • Product Design: The book covers major cloud platforms including AWS, Azure, and Google Cloud, as well as multicloud tools such as Snowflake and Databricks, offering broad and practical architectural coverage.

  • User Experience: Written to help professionals move efficiently from concept to deployment, this guide enables businesses to make data-driven decisions and deliver enterprise-wide intelligence in a fast and efficient way.

  • About the Author: Dr. Valliappa Lakshmanan is co-founder and CTO of Obin AI, a startup building deep domain AI agents for finance, where he sets the technology and science direction and leads product development.

  • Versatile Occasion: Suited to cloud professionals, data engineers, machine learning practitioners, and computer science students seeking a comprehensive and technically grounded reference.

  • Lifestyle Essential: Published by Books Kingdom and printed in India, this paperback is an essential resource for anyone looking to advance their expertise in modern data and AI platform architecture.

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