list-of-tables

List of Tables

 

Chapter 1. What is machine learning?

Table 1.1. Use cases for supervised machine learning, organized by the type of problem

Chapter 7. Advanced feature engineering

Table 7.1. Examples of color-range features. You add 1 to the divisors to avoid producing missing values from dividing by 0.

Table 7.2. Image metadata features that can be included in the ML pipeline

Table 7.3. San Francisco crime data in its raw form, as a sequence of events

Chapter 9. Scaling machine-learning workflows

Table 9.1. Problems in model building that can occur due to lack of scalability, plus their ultimate consequences

Table 9.2. Problems in ML prediction that can occur due to lack of scalability, plus their ultimate consequences