Who this book is for

This book is suitable for aspiring and actual data science practitioners, developers, and everyone who intends to work with large and complex datasets. We strive to make this book as accessible as possible to a wider audience. Yet, considering that the topics in this book are quite advanced, it is recommended, but not strictly compulsory, that readers are familiar with basic machine learning concept such as classification and regression, error minimizing functions, and cross validation.

We also assume some experience with Python, Jupyter Notebooks, and command-line execution together with a reasonable level of mathematical knowledge to grasp the concepts behind the various large solutions we propose. The text is written in a style that programmers of other languages (R, Java, and MATLAB) can follow. Ideally, it is highly suitable for (but not limited to) a data scientist familiar with machine learning and interested in leveraging Python, in respect to other languages such as R or MATLAB, because of its computational, memory, and I/O capabilities.