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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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Toc

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, we learned about SQL and NoSQL databases. Further, we introduced different databases, such as MySQL, MongoDB, and Cassandra, and implemented a hands-on experience to deal with real-world problems. Now we will extend our understanding of these databases and study the big data file formats.

Ever-growing competition in the industry has been reducing reaction times to nil and to keep up with this situation, businesses have to improvise their responses to the problems strategically. Businesses are continually facing challenges to improve the product offering, production, human resources, customer services, operations, and other facets of the business. To get a cutting edge over their competition, organizations have to apply many strategies, and analytics is one of the strategies that feeds on big data. A few companies that rely extensively on real-time big data applications are Facebook, Twitter, Apple, and Google.

Processing and analyzing this...

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