Artículo: AMZ-B0BG3FHSBX

Deep Credit Risk: Machine Learning in R

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Detalles del producto
Disponibilidad
Sin stock
Peso con empaque
0.84 kg
Devolución
No
Condición
Nuevo
Producto de
Amazon
Viaja desde
USA

Sobre este producto
  • www.deepcreditrisk.com provides real credit data, apps and much more. "Deep Credit Risk - Machine Learning in R" aims at starters and pros alike to enable you to: - Understand the role of liquidity, equity and many other key banking features - Engineer and select features - Predict defaults, payoffs, loss rates and exposures - Predict downturn and crisis outcomes using pre-crisis features - Understand the implications of COVID-19 - Apply innovative sampling techniques for model training and validation - Deep-learn from Logit Classifiers to Random Forests and Neural Networks - Do unsupervised Clustering, Principal Components and Bayesian Techniques - Build multi-period models for CECL, IFRS 9 and CCAR - Build credit portfolio correlation models for VaR and Expected Shortfall - Run over 1,500 lines of R code

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