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Machine Learning Engineering in Action

Jezik AngleščinaAngleščina
Knjiga Mehka
Knjiga Machine Learning Engineering in Action Ben Wilson
Koda Libristo: 36975700
Založba Manning Publications, april 2022
Field-tested tips, tricks, and design patterns for building MachineLearning projects that are deploy... Celoten opis
? points 153 b
63.19 €
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Field-tested tips, tricks, and design patterns for building MachineLearning projects that are deployable, maintainable, and secure from concept toproduction.
In Machine Learning Engineering inAction, you will learn:

 

  •        Evaluatingdata science problems to find the most effective solution
  •       Scopinga machine learning project for usage expectations and budget
  •       Processtechniques that minimize wasted effort and speed up production
  •       Assessinga project using standardized prototyping work and statistical validation
  •       Choosingthe right technologies and tools for your project
  •       Makingyour codebase more understandable, maintainable, and testable
  •       Automatingyour troubleshooting and logging practices

Databricks solutions architect BenWilson lays out an approach to building deployable, maintainable productionmachine learning systems. You''ll adopt software development standards thatdeliver better code management, and make it easier to test, scale, and evenreuse your machine learning code!

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O knjigi

Polni naslov Machine Learning Engineering in Action
Avtor Ben Wilson
Jezik Angleščina
Vezava Knjiga - Mehka
Datum izida 2022
Število strani 300
EAN 9781617298714
ISBN 1617298719
Koda Libristo 36975700
Založba Manning Publications
Teža 1026
Mere 235 x 187 x 39

Kategorije

Computing & Information Technology > Computer programming / software engineering > Software Engineering > Object oriented software engineering
Computing & Information Technology > Computer science > Artificial intelligence > Machine learning
Computing & Information Technology > Computer science > Artificial intelligence > Neural networks & fuzzy systems
Computing & Information Technology > Computer programming / software engineering > Object-oriented programming (OOP)
Computing & Information Technology > Databases > Data capture & analysis
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