Machine Learning, Animated - Couverture rigide

Liu, Mark

 
9781032462141: Machine Learning, Animated

Synopsis

The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. This book eases you into basic ML concepts and summarises the learning process in three words: initialize, adjust and repeat.

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À propos de l?auteur

Mark H. Liu is Associate Professor of Finance, (Founding) Director of MS Finance Program, University of Kentucky.
Mark is currently the director of Master of Science in Finance program at the University of Kentucky, U.S.A. He is also an associate professor of finance with tenure at the University of Kentucky.
He obtained his Ph.D. in finance from Boston College in 2004 and his M.A. in economics from Western University in Canada in 1998. His research interest is in machine learning and corporate finance. He has published his research in top finance journals such as Journal of Financial Economics, Journal of Financial and Quantitative Analysis, Journal of Corporate Finance, and Review of Corporate Finance Studies.
Dr. Mark Liu has run Python workshops for master students at the University of Kentucky in the last few years. He has incorporated Python in his teaching. In particular, he is now teaching a Python Predictive Analytics course to graduate students.
As the director of the MS Finance program, Mark has seen first-hand the high demand for machine learning skills in all industries. He has interacted with executives and recruiters from hundreds of companies, who in recent years have put an increasing emphasis on the importance of incorporating machine learning and data analytics skills in all business fields.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Autres éditions populaires du même titre

9781032462134: Machine Learning, Animated

Edition présentée

ISBN 10 :  1032462132 ISBN 13 :  9781032462134
Editeur : Chapman & Hall/CRC, 2025
Couverture souple