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DEEP CREDIT RISK
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Ready to BOOST your hands-on MACHINE LEARNING skills?

COVID-19 has created many challenges for credit risk analytics. Join our community of analysts who master Machine Learning in Python and R using real time credit data and thousands of code lines. What are you waiting for?

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"Deep Credit Risk — Machine Learning in Python and 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 value-at-risk and expected shortfall;
  • Detailed instructions and materials for new learners;
  • Run over 1,500 lines of code; and
  • Access real credit data and
  • ...much more …

Hands-on Machine Learning programming in PYTHON

Contents
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购书
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"It is bound to be of benefit to you whether you are a beginner
or a seasoned credit risk modeler."


- Anyruddho Sanyal, Owner, Phoenix Computing Solutions


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  • WELCOME
    • CONTENTS
    • START Python
    • START R
    • FEATURED
  • DATA & CODE
  • TRAINING
    • ONLINE
    • ZOOM MASTERCLASS
    • IN HOUSE
    • UNI
  • PAPERS
  • CONTACT
  • 中文