The item shows wear from consistent use, but it remains in good condition and works perfectly. All pages and cover are intact including the dust cover, if applicable . Spine may show signs of wear. Pages may include limited notes and highlighting. May NOT include discs, access code or other supplemental materials.

Seller Inventory # BVV.3319690132.G

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Bibliographic Details

Title: Machine-learning Techniques in Economics: New Tools for Predicting Economic Growth (SpringerBriefs in Economics)
Publisher: Springer
Publication Date: 2018
Language: English
ISBN 10: 3319690132
ISBN 13: 9783319690131
Binding: Soft cover
Condition: good

About this title

Synopsis

This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer economic questions. While machine learning itself is not a new idea, advances in computing technology combined with a dawning realization of its applicability to economic questions makes it a new tool for economists.

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