Concha Bielza, Pedro Larrañaga

Data-Driven Computational Neuroscience

Machine Learning and Statistical Models

• Gebundenes Buch

Produktbeschreibung

Trains researchers and graduate students in state-of-the-art statistical and machine learning methods to build models with real-world data.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 708
• Erscheinungstermin: 26. November 2020
• Englisch
• Abmessung: 257mm x 196mm x 43mm
• Gewicht: 1497g
• ISBN-13: 9781108493703
• ISBN-10: 110849370X
• Artikelnr.: 59483581

Autorenporträt

Concha Bielza is a professor in the Department of Artificial Intelligence at Universidad Politécnica de Madrid. She has published more than 120 journal papers and coauthored the book Industrial Applications of Machine Learning (2019). She was awarded the 2014 UPM Research Prize.

Inhaltsangabe

Part I. Introduction
Section 1. Computational Neuroscience
Part II. Statistics
Section 2. Exploratory Data Analysis
Section 3. Probability Theory and Random Variables
Section 4. Probabilistic Interference
Part III. Supervised pattern recognition
Section 5. Performance Evaluation
Section 6. Feature subset selection
Section 7. Non-probabilistic classifiers
Section 8. Probabilistic classifiers
Section 9. Metaclassifiers
Section 10. Multi-dimensional classifiers
Part IV. Unsupervised pattern recognition
Section 11. Non-probabilistic clustering
Section 12. Probabilistic clustering
Part V. Probabilistic graphical models
Section 13. Bayesian networks
Section 14. Markov networks
Part VI. Spatial statistics
Section 15. Spatial statistics.