Reliable machine learning: applying SRE principles to ML in production
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'...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Weitere beteiligte Personen: | , , , , |
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Sebastopol, CA
O'Reilly Media, Inc, USA
2022
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781098106218/?ar |
| Zusammenfassung: | 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. |
| Umfang: | 1 Online-Ressource |
| ISBN: | 1098106199 9781098106195 |
Internformat
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| spelling | Chen, Cathy VerfasserIn aut Reliable machine learning applying SRE principles to ML in production Cathy Chen, Niall Richard Murphy, Kranti Parisa, D. Sculley & Todd Underwood ; foreword by Sam Charrington Sebastopol, CA O'Reilly Media, Inc, USA 2022 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Machine learning Reliability (Engineering) Apprentissage automatique Fiabilité Murphy, Niall Richard MitwirkendeR ctb Parisa, Kranti MitwirkendeR ctb Sculley, D. MitwirkendeR ctb Underwood, Todd MitwirkendeR ctb Charrington, Sam MitwirkendeR ctb 1098106229 Erscheint auch als Druck-Ausgabe 1098106229 |
| spellingShingle | Chen, Cathy Reliable machine learning applying SRE principles to ML in production Machine learning Reliability (Engineering) Apprentissage automatique Fiabilité |
| title | Reliable machine learning applying SRE principles to ML in production |
| title_auth | Reliable machine learning applying SRE principles to ML in production |
| title_exact_search | Reliable machine learning applying SRE principles to ML in production |
| title_full | Reliable machine learning applying SRE principles to ML in production Cathy Chen, Niall Richard Murphy, Kranti Parisa, D. Sculley & Todd Underwood ; foreword by Sam Charrington |
| title_fullStr | Reliable machine learning applying SRE principles to ML in production Cathy Chen, Niall Richard Murphy, Kranti Parisa, D. Sculley & Todd Underwood ; foreword by Sam Charrington |
| title_full_unstemmed | Reliable machine learning applying SRE principles to ML in production Cathy Chen, Niall Richard Murphy, Kranti Parisa, D. Sculley & Todd Underwood ; foreword by Sam Charrington |
| title_short | Reliable machine learning |
| title_sort | reliable machine learning applying sre principles to ml in production |
| title_sub | applying SRE principles to ML in production |
| topic | Machine learning Reliability (Engineering) Apprentissage automatique Fiabilité |
| topic_facet | Machine learning Reliability (Engineering) Apprentissage automatique Fiabilité |
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