Practitioner's Introductory Guide to Data Science for Governance & Reporting

This book fills the need for a concise and conversational book on the growing field of Data Science. Easy to read and informative, this lucid book covers everything important, with concrete examples, and invites the reader to join this field. The chapters in the book are organized for a detailed step by step guide using real life example covering real data and help the reader the best way to report Management. This book is designed to provide a reader with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms. Finally, it includes a tutorial for R platform. .. Professionals in various domains, including executives, managers, analysts, professors, doctors, accountants, and others can use this book to learn in a few hours how to make sense of and develop actionable insights from the enormous data coming their way. This is a flowing book that one can finish in one sitting, or one can return to it again and again for insights and techniques. In the world of googling it, my belief that a book full of codes is of limited use but were to use the code and why and ability to explain to management is of more importance. hence I start this book by tips on delivering a good presentation so that all your hard work of analyzing data but bears sweet fruits as a good presentation is equally important as the analysis. however, in real life the process does not end there with you presenting your analysis. in fact it is the start of a series of follow up steps to make it into a successful outcome that why I also talk about actionable insights, I will try to introduce the challenges you might face in this project. obviously, these topics warrant a dedicated book on their own, hence I try to keep it simple and hope to provide introductory materials to get you going. I also included some common and niche machine learning model and also provide intuition behind it. I attempt to show that of all the various machine learning model it is an inference to a human problem-solving approach to certain situations and cannot be pure intelligence per se.