Deep Credit Risk: Machine Learning in R
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Deep Credit Risk: Machine Learning in R

by Harald Scheule, Daniel Rösch

Finance Machine Learning Credit Risk
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Deep Credit Risk: Machine Learning in R explores how machine learning and R can be applied to credit risk analysis. Harald Scheule and Daniel Rösch present a focused resource for readers seeking to connect data science, programming, and financial risk management.

ASIN B0BFWZHRX9 Views 94 Publisher Independently published Year 2022 Format Paperback Product Group Book Pages 493 Adult No Created March 03, 2026 Updated September 29, 2026
About This Book

Deep Credit Risk: Machine Learning in R focuses on the intersection of credit risk and machine learning.

The book connects financial risk analysis with the R programming language, offering a data-oriented perspective on modeling credit-related outcomes.

It is suited to readers interested in applying machine learning concepts within finance, banking, and credit risk management.

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