Analytical Skills for AI and Data Science
Data Science
Book Details
Book Title
Analytical Skills for AI and Data Science
Author
Daniel Vaughan
Publisher
O'Reilly Media, Inc, USA
Publication Date
2020
ISBN
9781492060949
Number of Pages
323
Language
English
Format
File Size
4.2MB
Subject
data-science
Table of Contents
- Preface
- 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?
- 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
- Business Questions and KPIs
- An Anatomy of a Decision: A Simple Decomposition
- A Primer on Causation
- Uncertainty
- 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
- Learning to Ask Business Questions: Examples from Common Use Cases
- Key Takeaways
- Further Reading
- 4. Actions, Levers, and Decisions
- Understanding What Is Actionable
- Physical Levers
- Human Levers
- Revisiting Our Use Cases
- Key Takeaways
- Further Reading
- 5. From Actions to Consequences: Learning How to Simplify
- Why Do We Need to Simplify?
- Exercising Our Analytical Muscle: Welcome Fermi
- Revisiting the Examples from Chapter 3
- Key Takeaways
- Further Reading
- 6. Uncertainty
- Where Does Uncertainty Come From?
- Quantifying Uncertainty
- Making Decisions Without Uncertainty
- Making Simple Decisions Under Uncertainty
- Decisions Under Uncertainty
- Normative and Descriptive Theories of Decision-Making
- Some Paradoxes in Decision-Making Under Uncertainty
- Putting it All into Practice
- Revisiting Our Use Cases
- Key Takeaways
- Further Reading
- 7. Optimization
- What Is Optimization?
- Optimization Without Uncertainty
- Optimization with Uncertainty
- Key Takeaways
- Further Reading
- 8. Wrapping Up
- Analytical Skills
- The AI-Driven Enterprise of the Future
- Some Final Thoughts
- A. A Brief Introduction to Machine Learning
- What Is Machine Learning?
- A Taxonomy of ML Models
- Regression and Classification
- Making Predictions
- From Linear Regression to Deep Learning
- A Primer on A/B Testing
- Further Reading
- Index