• Anglický jazyk

Agile Machine Learning

Autor: Matthew Hurst

Build resilient applied machine learning teams that deliver better data products through adapting the guiding principles of the Agile Manifesto.


Bringing together talented people to create a great applied machine learning team is no small feat.... Viac o knihe

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O knihe

Build resilient applied machine learning teams that deliver better data products through adapting the guiding principles of the Agile Manifesto.


Bringing together talented people to create a great applied machine learning team is no small feat. With developers and data scientists both contributing expertise in their respective fields, communication alone can be a challenge. Agile Machine Learning teaches you how to deliver superior data products through agile processes and to learn, by example, how to organize and manage a fast-paced team challenged with solving novel data problems at scale, in a production environment.


The authors' approach models the ground-breaking engineering principles described in the Agile Manifesto. The book provides further context, and contrasts the original principles with the requirements of systems that deliver a data product.


What You'll Learn


Effectively run a data engineering team that is metrics-focused, experiment-focused, and data-focused

Make sound implementation and model exploration decisions based on the data and the metrics

Know the importance of data wallowing: analyzing data in real time in a group setting

Recognize the value of always being able to measure your current state objectively

Understand data literacy, a key attribute of a reliable data engineer, from definitions to expectations


















Who This Book Is For
Anyone who manages a machine learning team, or is responsible for creating production-ready inference components. Anyone responsible for data project workflow of sampling data; labeling, training, testing, improving, and maintaining models; and system and data metrics will also find this book useful. Readers should be familiar with software engineering and understand the basics of machine learning and working with data.

  • Vydavateľstvo: Apress
  • Rok vydania: 2019
  • Formát: Paperback
  • Rozmer: 254 x 178 mm
  • Jazyk: Anglický jazyk
  • ISBN: 9781484251065

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