Trains researchers and graduate students in state-of-the-art statistical and machine learning methods to build models with real-world data.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
