Automated machine learning for business / Kai R. Larsen, Daniel S. Becker.

Format:

Book

Author/Creator:

Larsen, Kai R., author.

Becker, Daniel S., author.

Language:

English

Subjects (All):

Machine learning--Industrial applications--Textbooks.

Machine learning.

Decision making--Statistical methods--Textbooks.

Decision making.

Business planning--Statistical methods--Textbooks.

Business planning.

Business planning--Data processing--Textbooks.

Physical Description:

1 online resource (xvii, 328 pages) : color illustrations.

Place of Publication:

New York : Oxford University Press, [2021]

Summary:

This book teaches the full process of how to conduct machine learning in an organizational setting. It develops the problem-solving mind-set needed for machine learning and takes the reader through several exercises using an automated machine learning tool. To build experience with machine learning, the book provides access to the industry-leading AutoML tool, DataRobot, and provides several data sets designed to build deep hands-on knowledge of machine learning.

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.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9780190941673

0-19-760149-9

0-19-094168-5

OCLC:

1227855732