www.deepcreditrisk.com provides real credit data, apps and much more."Deep Credit Risk - Machine Learning with 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
✔ Author(s): Daniel Rösch,Harald Scheule
✔ Title: Deep Credit Risk: Machine Learning with Python
✔ Rating : 4 out of 5 base on (21 reviews)
✔ ISBN-10: B08BV3KQG7
✔ Language: English
✔ Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
✔ Device compatibles: Android, iOS, PC and Amazon Kindle
Readers' opinions about Deep Credit Risk by Daniel Rösch
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