AI and Big Data on IBM Power Systems Servers Book Reviews

AUTHOR
Scott Vetter, Ivaylo B. Bozhinov, Anto A John, Rafael Freitas de Lima, Ahmed.(Mash) Mashhour, James Van Oosten, Fernando Vermelho & Allison White
SCORE
0
TOTAL RATINGS
102

AI and Big Data on IBM Power Systems Servers by Scott Vetter, Ivaylo B. Bozhinov, Anto A John, Rafael Freitas de Lima, Ahmed.(Mash) Mashhour, James Van Oosten, Fernando Vermelho & Allison White Book Summary

As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning (ML) and deep learning (DL) in big data environments can identify historical patterns and build artificial intelligence (AI) models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business (LOBs), and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available for integration with their data lake environments.

In this IBM® Redbooks® publication, we cover the best practices for deploying and integrating some of the best AI solutions on the market, including:

IBM Watson Machine Learning Accelerator (see note for product naming)
IBM Watson Studio Local
IBM Power Systems™
IBM Spectrum™ Scale
IBM Data Science Experience (IBM DSX)
IBM Elastic Storage™ Server
Hortonworks Data Platform (HDP)
Hortonworks DataFlow (HDF)
H2O Driverless AI

We map out all the integrations that are possible with our different AI solutions and how they can integrate with your existing or new data lake. We also walk you through some of our client use cases and show you how some of the industry leaders are using Hortonworks, IBM PowerAI, and IBM Watson Studio Local to drive decision making. We also advise you on your deployment options, when to use a GPU, and why you should use the IBM Elastic Storage Server (IBM ESS) to improve storage management. Lastly, we describe how to integrate IBM Watson Machine Learning Accelerator and Hortonworks with or without IBM Watson Studio Local, how to access real-time data, and security.
Note: IBM Watson Machine Learning Accelerator is the new product name for IBM PowerAI Enterprise.

Note: Hortonworks merged with Cloudera in January 2019. The new company is called Cloudera. References to Hortonworks as a business entity in this publication are now referring to the merged company. Product names beginning with Hortonworks continue to be marketed and sold under their original names.

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Book Name AI and Big Data on IBM Power Systems Servers
Genre Computers
Published
Language English
E-Book Size 4.08 MB

AI and Big Data on IBM Power Systems Servers (Scott Vetter, Ivaylo B. Bozhinov, Anto A John, Rafael Freitas de Lima, Ahmed.(Mash) Mashhour, James Van Oosten, Fernando Vermelho & Allison White) Book Reviews 2024

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Summary of AI and Big Data on IBM Power Systems Servers by Scott Vetter, Ivaylo B. Bozhinov, Anto A John, Rafael Freitas de Lima, Ahmed.(Mash) Mashhour, James Van Oosten, Fernando Vermelho & Allison White

The AI and Big Data on IBM Power Systems Servers book written by Scott Vetter, Ivaylo B. Bozhinov, Anto A John, Rafael Freitas de Lima, Ahmed.(Mash) Mashhour, James Van Oosten, Fernando Vermelho & Allison White was published on 10 April 2019, Wednesday in the Computers category. A total of 102 readers of the book gave the book 0 points out of 5.

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