"A playbook for bridging business and data science worlds to effectively execute machine learning projects in business"--Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Eric Siegel is a leading consultant and former Columbia University and UVA Darden professor. He is the founder of the long-running Machine Learning Week conference series, a frequent keynote speaker, and author of the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.
Inhaltsangabe
Contents Series Foreword ix Foreword by Morgan Vawter xi Preface: A Brief History of Why Machine Learning Projects Stall xv Optional FAQ: What This Book Is about and Who It’s For xxi Introduction 1 0 BizML: Six Steps to Machine Learning Deployment 21 1 Value: Establish the Deployment Goal 49 2 Target: Establish the Prediction Goal 63 3 Performance: Establish the Evaluation Metrics 81 4 Fuel: Prepare the Data 113 5 Algorithm: Train the Model 141 6 Launch: Deploy the Model 169 BizML Cheat Sheet 195 Conclusion: ML’s Elevator Pitch, Staff, Timeline, Upkeep, and Ethics 197 Acknowledgments 213 About the Author 217 Index 219
Contents Series Foreword ix Foreword by Morgan Vawter xi Preface: A Brief History of Why Machine Learning Projects Stall xv Optional FAQ: What This Book Is about and Who It’s For xxi Introduction 1 0 BizML: Six Steps to Machine Learning Deployment 21 1 Value: Establish the Deployment Goal 49 2 Target: Establish the Prediction Goal 63 3 Performance: Establish the Evaluation Metrics 81 4 Fuel: Prepare the Data 113 5 Algorithm: Train the Model 141 6 Launch: Deploy the Model 169 BizML Cheat Sheet 195 Conclusion: ML’s Elevator Pitch, Staff, Timeline, Upkeep, and Ethics 197 Acknowledgments 213 About the Author 217 Index 219
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