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About this product
Product Information
Deep Credit Risk - Machine Learning in Python 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 pandas, statsmodels and scikit-learn Python code- Access real credit data and much more ...Product Identifiers
PublisherIndependently Published
ISBN-139798617590199
eBay Product ID (ePID)19049055385
Product Key Features
SubjectFinance
Publication Year2020
Number of Pages470 Pages
Publication NameDeep Credit Risk: Machine Learning with Python
LanguageEnglish
TypeTextbook
AuthorHarald Scheule, Daniel Roesch
FormatPaperback
Dimensions
Item Height235 mm
Item Weight798 g
Item Width191 mm
Additional Product Features
Title_AuthorHarald Scheule, Daniel Roesch
