Machine-learning Techniques in Economics
New Tools for Predicting Economic Growth
(Sprache: Englisch)
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...
Voraussichtlich lieferbar in 3 Tag(en)
versandkostenfrei
Buch (Kartoniert)
Fr. 77.00
inkl. MwSt.
- Kreditkarte, Paypal, Rechnungskauf
- 30 Tage Widerrufsrecht
Produktdetails
Produktinformationen zu „Machine-learning Techniques in Economics “
Klappentext zu „Machine-learning Techniques in Economics “
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. Inhaltsverzeichnis zu „Machine-learning Techniques in Economics “
Why this Book?.- Data, Variables, and Their Sources.- Methodology.- Predicting Economic Growth: A First Look.- Predicting Economic Growth: Which Variables Matter?.- Predicting Recessions: What We Learn from Widening the Goalposts.- Epilogue.
Bibliographische Angaben
- Autoren: Atin Basuchoudhary , James T. Bang , Tinni Sen
- 2018, 1st ed. 2017, VI, 94 Seiten, 19 farbige Abbildungen, Masse: 15,6 x 23,6 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3319690132
- ISBN-13: 9783319690131
- Erscheinungsdatum: 08.01.2018
Sprache:
Englisch
Kommentar zu "Machine-learning Techniques in Economics"
0 Gebrauchte Artikel zu „Machine-learning Techniques in Economics“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Machine-learning Techniques in Economics".
Kommentar verfassen