Before diving into the management issues of building systems around machine learning algorithms, we need to explore the topic of data science itself. What are the main concepts behind data science and machine learning? How do you build and test a model? What are the common pitfalls in this process? What kinds of models are there? What tasks can we solve using machine learning?
This section contains the following chapters:
- Chapter 1, What You Can Do with Data Science
- Chapter 2, Testing Your Models
- Chapter 3, Understanding AI
