Masís Interpretable Machine Learning with Python

Learn to build interpretable high-performance models with hands-on real-world examples
1. Auflage 2021
ISBN: 978-1-80020-657-1
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 736 Seiten

No detailed description available for "Interpretable Machine Learning with Python".

Autoren/Hrsg.

Masís, Serg

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computersimulation & Modelle, 3-D Graphik

Inhaltsverzeichnis

Table of Contents - Interpretation, Interpretability and Explainability; and why does it all matter?
- Key Concepts of Interpretability
- Interpretation Challenges
- Fundamentals of Feature Importance and Impact
- Global Model-Agnostic Interpretation Methods
- Local Model-Agnostic Interpretation Methods
- Anchor and Counterfactual Explanations
- Visualizing Convolutional Neural Networks
- 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?

Über Autor(innen)

Masís Serg:

Serg Masís has been at the confluence of the internet, application development, and analytics for the last two decades. Currently, he's a climate and agronomic data scientist at Syngenta, a leading agribusiness company with a mission to improve global food security. Before that role, he co-founded a start-up, incubated by Harvard Innovation Labs, that combined the power of cloud computing and machine learning with principles in decision-making science to expose users to new places and events. Whether it pertains to leisure activities, plant diseases, or customer lifetime value, Serg is passionate about providing the often-missing link between data and decision-making—and machine learning interpretation helps bridge this gap robustly.