Analytical Skills for AI and Data Science : Building Skills for an AI-Driven Enterprise.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Vaughan, Daniel
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Sebastopol : O'Reilly Media, Incorporated, 2020.
Temas:
Business > Data processing.
Artificial intelligence.
Artificial Intelligence
Gestion > Informatique.
Intelligence artificielle.
artificial intelligence.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Intro
  • Preface
  • Why Analytical Skills for AI?
  • Use Case-Driven Approach
  • What This Book Isn't
  • Who This Book Is For
  • What's Needed
  • Conventions Used in This Book
  • Using Code Examples
  • O'Reilly Online Learning
  • How to Contact Us
  • Acknowledgments
  • 1. Analytical Thinking and the AI-Driven Enterprise
  • What Is AI?
  • Why Current AI Won't Deliver on Its Promises
  • How Did We Get Here?
  • The Data Revolution
  • The three Vs
  • Data maturity models
  • Descriptive stage
  • Predictive stage
  • Prescriptive stage
  • A Tale of Unrealized Expectations
  • Analytical Skills for the Modern AI-Driven Enterprise
  • Key Takeways
  • Further Reading
  • 2. Intro to Analytical Thinking
  • Descriptive, Predictive, and Prescriptive Questions
  • When Predictive Analysis Is Powerful: The Case of Cancer Detection
  • Descriptive Analysis: The Case of Customer Churn
  • Describing churn
  • Predicting churn
  • Prescribing courses of action to reduce churn
  • Business Questions and KPIs
  • KPIs to Measure the Success of a Loyalty Program
  • An Anatomy of a Decision: A Simple Decomposition
  • An Example: Why Did You Buy This Book?
  • A Primer on Causation
  • Defining Correlation and Causation
  • Some Difficulties in Estimating Causal Effects
  • Problem 1: We can't observe counterfactuals
  • Problem 2: Heterogeneity
  • Problem 3: Confounders
  • Problem 4: Selection effects
  • A/B testing
  • Uncertainty
  • Uncertainty from Simplification
  • Uncertainty from Heterogeneity
  • Uncertainty from Social Interactions
  • Uncertainty from Ignorance
  • Key Takeaways
  • Further Reading
  • 3. Learning to Ask Good Business Questions
  • From Business Objectives to Business Questions
  • Descriptive, Predictive, and Prescriptive Questions
  • Always Start with the Business Question and Work Backward
  • Further Deconstructing the Business Questions
  • Example with a Two-Sided Platform
  • Learning to Ask Business Questions: Examples from Common Use Cases
  • Lowering Churn
  • Defining the business question
  • Descriptive questions
  • Predictive questions
  • Prescriptive questions
  • Cross-Selling: Next-Best Offer
  • Defining the business question
  • Descriptive questions
  • Predictive questions
  • Prescriptive questions
  • CAPEX Optimization
  • Store Locations
  • Who Should I Hire?
  • Delinquency Rates
  • Stock or Inventory Optimization
  • Store Staffing
  • Key Takeaways
  • Further Reading
  • 4. Actions, Levers, and Decisions
  • Understanding What Is Actionable
  • Physical Levers
  • Human Levers
  • Why Do We Behave the Way We Do?
  • Levers from Restrictions
  • Time restrictions
  • Levers That Affect Our Preferences
  • Genetics
  • Individual and social learning
  • Social reasons: strategic effects
  • Social reasons: conformity and peer effects
  • Framing effects
  • Loss aversion
  • Levers That Change Your Expectations
  • The availability and representativeness heuristics
  • Revisiting Our Use Cases
  • Customer Churn
  • Cross-Selling
  • Analytical thinking and the AI-driven enterprise
  • Intro to analytical thinking
  • Learning to ask good business questions
  • Actions, levers, and decisions
  • From actions to consequences: learning how to simplify
  • Uncertainity
  • Optimization
  • Wrapping up.

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