Machine Learning and Data Analytics for Solving Business Problems - Methods, Applications, and Case Studies (Hardcover, 1st ed. 2022)


This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods - such as blockchain, big data, artificial intelligence, and cloud computing - so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems.

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Product Description

This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods - such as blockchain, big data, artificial intelligence, and cloud computing - so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems.

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Product Details

General

Imprint

Springer International Publishing AG

Country of origin

Switzerland

Series

Unsupervised and Semi-Supervised Learning

Release date

December 2022

Availability

Expected to ship within 12 - 17 working days

First published

2022

Editors

, , ,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

206

Edition

1st ed. 2022

ISBN-13

978-3-03-118482-6

Barcode

9783031184826

Categories

LSN

3-03-118482-3



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