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
✔ ISBN-13: 978B08BV3KQG5
✔ 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
Beata Shepard
I'm still in awe of the intricate plot and the way everything seamlessly came together. The twists kept me guessing until the very end. It's one of those rare books that leave a lasting impact.
Katherine Stevenson
What an intellectual journey! The themes explored in this book challenged my perceptions and sparked introspection. It's refreshing to read a book that provokes such thought.
Aileen Menzie
The plot was incredibly well-crafted, with twists and turns that kept me hooked until the very last page. It was impossible to predict what would happen next.
