Applied Machine Learning

• Κύριος συγγραφέας: Forsyth, David (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Θέματα: Artificial intelligence.; Mathematical statistics.; Artificial Intelligence.; Probability and Statistics in Computer Science.

Machine learning methods are now an important tool for scientists, researchers, engineers and students in a wide range of areas. This book is written for people who want to adopt and use the main tools of machine learning, but aren't necessarily going to want to be machine learning researchers....

Πίνακας περιεχομένων:

• 1. Learning to Classify
• 2. SVM's and Random Forests
• 3. A Little Learning Theory
• 4. High-dimensional Data
• 5. Principal Component Analysis
• 6. Low Rank Approximations
• 7. Canonical Correlation Analysis
• 8. Clustering
• 9. Clustering using Probability Models
• 10. Regression
• 11. Regression: Choosing and Managing Models
• 12. Boosting
• 13. Hidden Markov Models
• 14. Learning Sequence Models Discriminatively
• 15. Mean Field Inference
• 16. Simple Neural Networks
• 17. Simple Image Classifiers
• 18. Classifying Images and Detecting Objects
• 19. Small Codes for Big Signals
• Index.