Information-Driven Machine Learning : Data Science as an Engineering Discipline 9783031394775, 9783031394768

This groundbreaking book transcends traditional machine learning approaches by introducing information measurement metho

117 25 13MB

English Pages 289 Year 2023

Table of contents :
Cover
Front Matter
1. Introduction
2. The Automated Scientific Process
3. The (Black Box) Machine Learning Process
4. Information Theory
5. Capacity
6. The Mechanics of Generalization
7. Meta-Math: Exploring the Limits of Modeling
8. Capacity of Neural Networks
9. Neural Network Architectures
10. Capacities of Some Other Machine Learning Methods
11. Data Collection and Preparation
12. Measuring Data Sufficiency
13. Machine Learning Operations
14. Explainability
15. Repeatability and Reproducibility
16. The Curse of Training and the Blessing of High Dimensionality
17. Machine Learning and Society
Back Matter

Information-Driven Machine Learning : Data Science as an Engineering Discipline
9783031394775, 9783031394768

Author / Uploaded
Gerald Friedland

Similar Topics
Computers
Algorithms and Data Structures: Pattern Recognition

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