Automated machine learning for business [electronic resource] / Kai R. Larsen and Daniel S. Becker.

"In this book, we teach the machine learning process using a new development in data science; automated machine learning. AutoML, when implemented properly, makes machine learning accessible to most people because it removes the need for years of experience in the most arcane aspects of data science...

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Bibliographic Details
Main Authors: Larsen, Kai R. (Author)
Becker, Daniel S. (Author)
Language:English
Published: New York, NY : Oxford University Press, [2021]
Subjects:
Business planning > Data processing > Textbooks.
Business planning > Statistical methods > Textbooks.
Machine learning > Industrial applications > Textbooks.
Decision making > Statistical methods > Textbooks.
Genre:
Textbooks.
Online Access:
Oxford Scholarship Online 2021: 2021 (Oxford Academic)
University Press Scholarship Online Complete Collection: 2021 (Oxford Academic)
Oxford Scholarship Online: 2021 (Oxford Academic)
Format: Electronic eBook
Contents:
  • What is machine learning?
  • Automating machine learning
  • Specify business problem
  • Acquire subject matter expertise
  • Define prediction target
  • Decide on unit of analysis
  • Success, risk, and continuation
  • Accessing and storing data
  • Data integration
  • Data transformations
  • Summarization
  • Data reduction and splitting
  • Startup processes
  • Feature understanding and selection
  • Build candidate models
  • Understanding the process
  • Evaluate model performance
  • Comparing model pairs
  • Interpret model
  • Communicate model insights
  • Set up prediction system
  • Document modeling process for reproducibility
  • Create model monitoring and maintenance plan
  • Seven types of target leakage in machine learning and an exercise
  • Time-aware modeling
  • Time-series modeling.