1st Edition
Data Science for Water Utilities Data as a Source of Value
1. Introduction to Data Science 2. Basics of the R Language 3. Loading and Exploring Data 4. Descriptive Statistics 5. Visualising Data with ggplot2 6. Sharing Results 7. Managing Dirty Data 8. Analysing the Customer Experience 9. Basic Linear Regression 10. Clustering Customers to Define Segments 11. Working with Dates and Times 12. Detecting Outliers and Anomalies 13. Introduction to Machine Learning
Biography
Peter Prevos is a civil engineer and social scientist who manages the data science function at Coliban Water in regional Australia. Peter has three decades of experience in water management in Europe, Asia and Australia. He promotes creating value from data using code. He is the author of several books and runs leading courses in data science for water professionals.
