Analytical Skills for AI and Data Science

Index

A

• A/B testing
  • about, A/B testing, A/B testing
  • books on, Further Reading
  • causality testing, Understanding Causality
  • ethical considerations, Ethics
  • false positives and negatives, False positives and false negatives
  • false positives/negatives costs, False positives and false negatives
  • in practice, A/B testing in practice
  • power and size calculations, Understanding power and size calculations
  • probability estimates via, A/B testing
  • sample size selection, False positives and false negatives
  • selection bias minimization, A/B testing, A/B testing, A Primer on A/B Testing
• acceptable waiting time (AWT), Optimal Staffing
• actionable insights
  • as goal, Always Start with the Business Question and Work Backward
  • data providing, Describing churn
  • levers for action, Understanding What Is Actionable
    • (see also levers)
• actionable questions from decomposition, Further Deconstructing the Business Questions
• actions (see levers)
• activation functions, Activation functions: adding some extra nonlinearity
• advertising (see marketing)
• Agile movement, From Business Objectives to Business Questions
• AI (see artificial intelligence)
• AlexNet neural network, The success of deep learning
• algorithms
  • deep learning, What Is AI?, From Linear Regression to Deep Learning-The success of deep learning
    • (see also deep learning)
  • definition, What Is Machine Learning?
  • learning how to make decisions, Learning how to make decisions
  • optimization, What Is Optimization?
  • outlier sensitivity, Making Good Predictions
  • predictions in AI, What Is AI?, Back to AI, Making ...