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Interpretable Machine Learning with Python - Second Edition

You're reading from  Interpretable Machine Learning with Python - Second Edition

Product type Book
Published in Oct 2023
Publisher Packt
ISBN-13 9781803235424
Pages 606 pages
Edition 2nd Edition
Languages
Author (1):
Serg Masís Serg Masís
Profile icon Serg Masís

Table of Contents (17) Chapters

Preface Interpretation, Interpretability, and Explainability; and Why Does It All Matter? Key Concepts of Interpretability Interpretation Challenges Global Model-Agnostic Interpretation Methods Local Model-Agnostic Interpretation Methods Anchors and Counterfactual Explanations Visualizing Convolutional Neural Networks Interpreting NLP Transformers Interpretation Methods for Multivariate Forecasting and Sensitivity Analysis Feature Selection and Engineering for Interpretability Bias Mitigation and Causal Inference Methods Monotonic Constraints and Model Tuning for Interpretability Adversarial Robustness What’s Next for Machine Learning Interpretability? Other Books You May Enjoy
Index

The mission

It has been estimated that there are over 10 million non-profits worldwide, and while a large portion of them have public funding, most of them depend mostly on private donors, both corporate and individual, to continue operations. As such, fundraising is mission-critical and carried out throughout the year.

Year over year, donation revenue has grown, but there are several problems non-profits face: donor interests evolve, so a charity popular one year might be forgotten the next; competition is fierce between non-profits, and demographics are shifting. In the United States, the average donor only gives two charitable gifts per year and is over 64 years old. Identifying potential donors is challenging, and campaigns to reach them can be expensive.

A National Veterans Organization non-profit arm has a large mailing list of about 190,000 past donors and would like to send a special mailer to ask for donations. However, even with a special bulk discount rate, it costs...

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