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Introduction
PART I: PROLOGUE, AND NEIGHBORHOOD-BASED METHODS
Chapter 1: Regression Models
Chapter 2: Classification Models
Chapter 3: Bias, Variance, Overfitting, and Cross-Validation
Chapter 4: Dealing with Large Numbers of Features
PART II: TREE-BASED METHODS
Chapter 5: A Step Beyond k-NN: Decision Trees
Chapter 6: Tweaking the Trees
Chapter 7: Finding a Good Set of Hyperparameters
PART III: METHODS BASED ON LINEAR RELATIONSHIPS
Chapter 8: Parametric Methods
Chapter 9: Cutting Things Down to Size: Regularization
PART IV: METHODS BASED ON SEPARATING LINES AND PLANES
Chapter 10: A Boundary Approach: Support Vector Machines
Chapter 11: Linear Models on Steroids: Neural Networks
PART V: APPLICATIONS
Chapter 12: Image Classification
Chapter 13: Handling Time Series and Text Data
Appendix A: List of Acronyms and Symbols
Appendix B: Statistics and ML Terminology Correspondence
Appendix C: Matrices, Data Frames, and Factor Conversions
Appendix D: Pitfall: Beware of “p-Hacking”!
| Erscheinungsjahr: | 2024 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 242 |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9781718502109 |
| ISBN-10: | 1718502109 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Matloff, Norman |
| Hersteller: |
Random House LLC US
No Starch Press |
| Maße: | 235 x 180 x 20 mm |
| Von/Mit: | Norman Matloff |
| Erscheinungsdatum: | 09.01.2024 |
| Gewicht: | 0,534 kg |
Introduction
PART I: PROLOGUE, AND NEIGHBORHOOD-BASED METHODS
Chapter 1: Regression Models
Chapter 2: Classification Models
Chapter 3: Bias, Variance, Overfitting, and Cross-Validation
Chapter 4: Dealing with Large Numbers of Features
PART II: TREE-BASED METHODS
Chapter 5: A Step Beyond k-NN: Decision Trees
Chapter 6: Tweaking the Trees
Chapter 7: Finding a Good Set of Hyperparameters
PART III: METHODS BASED ON LINEAR RELATIONSHIPS
Chapter 8: Parametric Methods
Chapter 9: Cutting Things Down to Size: Regularization
PART IV: METHODS BASED ON SEPARATING LINES AND PLANES
Chapter 10: A Boundary Approach: Support Vector Machines
Chapter 11: Linear Models on Steroids: Neural Networks
PART V: APPLICATIONS
Chapter 12: Image Classification
Chapter 13: Handling Time Series and Text Data
Appendix A: List of Acronyms and Symbols
Appendix B: Statistics and ML Terminology Correspondence
Appendix C: Matrices, Data Frames, and Factor Conversions
Appendix D: Pitfall: Beware of “p-Hacking”!
| Erscheinungsjahr: | 2024 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 242 |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9781718502109 |
| ISBN-10: | 1718502109 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Matloff, Norman |
| Hersteller: |
Random House LLC US
No Starch Press |
| Maße: | 235 x 180 x 20 mm |
| Von/Mit: | Norman Matloff |
| Erscheinungsdatum: | 09.01.2024 |
| Gewicht: | 0,534 kg |
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