Preface

When facing a business problem, machine learning allows you to develop powerful and effective data-driven solutions. The recent explosion of data volume and sources increased the effectiveness of solutions based on data, so this field is becoming more and more valuable. Developing a machine learning solution has specific requirements, and there are some software and tools that support it. A very good option is to use R, which is an open source programming language for statistics supported by a wide international community. The R structure is projected for statistical analysis, and the international community develops the most cutting-edge solutions. For these reasons, R allows you to develop powerful machine learning solutions using just a few lines of code.

There are machine learning tutorials, and they usually require some knowledge of the basics of statistics and computer science. This book is not just a tutorial. It doesn't even require a strong background in statistics or computer science. The target is not to provide you with a complete overview of all the techniques or to teach you how to build sophisticated solutions. This book is a path full of hands-on examples that provide you with the expertise to build a solution to a new problem. The aim is to show the most important concepts behind the approach in such a way that you have a deep understanding of machine learning and are able to identify and use the new algorithms.