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    Deep Credit Risk: Machine Learning with Python

    Beschreibung Deep Credit Risk: Machine Learning with Python. 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 …



    Buch Deep Credit Risk: Machine Learning with Python PDF ePub

    : Deep Credit Risk: Machine Learning with Python ~ 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 .

    DEEP CREDIT RISK - WELCOME ~ "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 .

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    CONTENTS - DEEP CREDIT RISK ~ Python Literacy; Risk-Based Learning; Machine Learning; Data Processing and Validation. Outcome Engineering; Feature Engineering; Feature Selection ; Validation; Default, Payoff, LGD and EAD Modeling. Default Modeling; Payoff Modeling; LGD Modeling; Exposure Modeling; Deep Credit Risk: Machine Learning with Python. Machine Learning for PD and LGD Forecasting. Standalone Techniques; Neural .

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