The Data Science Design Manual

This book serves an introduction to data science, focusing on the skills and principles needed to build systems for collecting, analyzing, and interpreting data. As a discipline, data science sits at the intersection of statistics, computer science, and machine learning, but it is building a distinct heft and character of its own.

In particular, the book stresses the following basic principles as fundamental to becoming a good data scientist: ¿Valuing Doing the Simple Things Right¿, laying the groundwork of what really matters in analyzing data; ¿Developing Mathematical Intuition¿, so that readers can understand on an intuitive level why these concepts were developed, how they are useful and when they work best, and; ¿Thinking Like a Computer Scientist, but Acting Like a Statistician¿, following approaches which come most naturally to computer scientists while maintaining the core values of statistical reasoning. The book does not emphasize any particular language or suite of dat