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Reliable Machine Learning

(ebook) (audiobook) (audiobook) Książka w języku angielskim
Reliable Machine Learning Cathy Chen, Niall Richard Murphy, Kranti Parisa - okladka książki

Reliable Machine Learning Cathy Chen, Niall Richard Murphy, Kranti Parisa - okladka książki

Reliable Machine Learning Cathy Chen, Niall Richard Murphy, Kranti Parisa - audiobook MP3

Reliable Machine Learning Cathy Chen, Niall Richard Murphy, Kranti Parisa - audiobook CD

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(211,65 zł najniższa cena z 30 dni)

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Do przechowalni

Whether you're part of a small startup or a multinational corporation, this practical book shows data scientists, software and site reliability engineers, product managers, and business owners how to run and establish ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization.

By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guest authors show you how to run an efficient and reliable ML system. Whether you want to increase revenue, optimize decision making, solve problems, or understand and influence customer behavior, you'll learn how to perform day-to-day ML tasks while keeping the bigger picture in mind.

You'll examine:

  • What ML is: how it functions and what it relies on
  • Conceptual frameworks for understanding how ML "loops" work
  • How effective productionization can make your ML systems easily monitorable, deployable, and operable
  • Why ML systems make production troubleshooting more difficult, and how to compensate accordingly
  • How ML, product, and production teams can communicate effectively

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O autorze książki

Kranti Parisa has more than a decade of software development expertise and a deep understanding of open source, enterprise software, and the execution required to build successful products. He has fallen in love with enterprise search technologies, especially Lucene and Solr, after his initial implementations and customizations carried out in early 2008 to build a legal search engine for bankruptcy court documents, docket entries, and cases. He is an active contributor to the Apache Solr community. One of his recent contributions, along with Joel Bernstein, SOLR-4787, includes scalable and nested join implementations. Kranti is currently working at Apple. Prior to that, he worked as a lead engineer and search architect at Comcast Labs, building and supporting a highly scalable search and discovery engine for the X1/X2 platformthe world's first entertainment operating system. An entrepreneur by DNA, he is the cofounder and technical advisor of multiple start-ups focusing on cloud computing, SaaS, big data, and enterprise search based products and services. He holds a master's degree in computer integrated manufacturing from the National Institute of Technology, Warangal, India. You can reach him on LinkedIn: http://www.linkedin.com/in/krantiparisa.

Cathy Chen, Niall Richard Murphy, Kranti Parisa - pozostałe książki

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