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The Artificial Intelligence Infrastructure Workshop

You're reading from   The Artificial Intelligence Infrastructure Workshop Build your own highly scalable and robust data storage systems that can support a variety of cutting-edge AI applications

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781800209848
Length 732 pages
Edition 1st Edition
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Authors (6):
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Bas Geerdink Bas Geerdink
Author Profile Icon Bas Geerdink
Bas Geerdink
Chinmay Arankalle Chinmay Arankalle
Author Profile Icon Chinmay Arankalle
Chinmay Arankalle
Kunal Gera Kunal Gera
Author Profile Icon Kunal Gera
Kunal Gera
Kevin Liao Kevin Liao
Author Profile Icon Kevin Liao
Kevin Liao
Gareth Dwyer Gareth Dwyer
Author Profile Icon Gareth Dwyer
Gareth Dwyer
Anand N.S. Anand N.S.
Author Profile Icon Anand N.S.
Anand N.S.
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Table of Contents (14) Chapters Close

Preface
1. Data Storage Fundamentals 2. Artificial Intelligence Storage Requirements FREE CHAPTER 3. Data Preparation 4. The Ethics of AI Data Storage 5. Data Stores: SQL and NoSQL Databases 6. Big Data File Formats 7. Introduction to Analytics Engine (Spark) for Big Data 8. Data System Design Examples 9. Workflow Management for AI 10. Introduction to Data Storage on Cloud Services (AWS) 11. Building an Artificial Intelligence Algorithm 12. Productionizing Your AI Applications Appendix

Introduction

In the previous chapter, you learned how to use Apache Spark to process large amounts of data in a pipeline architecture. We'll be looking at a pipeline design again in this chapter and see how we can use pipelines as a powerful system design.

Between 1998 and 2005, the US Navy spent over $1 billion on four separate attempts to implement an Enterprise Resource Planning (ERP) system based on SAP AG software. These efforts were regarded as failures, with nearly no value to show for the money that was spent. This shows why having proper designs and plans in place is important, and what can go wrong if the implementation of a system is started before a proper plan is created. Bad design and planning are such a common problem in the software engineering industry that it has led to the much-quoted joke, "A few weeks of coding can save you hours of planning."

While it's often tempting to start building systems from the get-go, this approach makes it...

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