Preface

We are at an interesting juncture in the evolution of the digital age, where there is an enormous amount of computing power and data in the hands of everyone. There has been an exponential growth in the amount of data we now have in digital form. While being associated with data-related technologies for more than 6 years, we have seen a rapid shift towards enterprises  that are willing to leverage data assets initially for insights and eventually for advanced analytics. What sounded like hype initially has become a reality in a very short period of time. Most companies have realized that data is the most important asset needed to stay relevant. As practitioners in the big data analytics industry, we have seen this shift very closely by working with many clients of various sizes, across regions and functional domains. There is a common theme evolving toward open distributed open source computing to store data assets and perform advanced analytics to predict future trends and risks for businesses.

This book is an attempt to share the knowledge we have acquired over time to help new entrants in the big data space to learn from our experience. We realize that the field of artificial intelligence is vast and it is just the beginning of a revolution in the history of mankind. We are going to see AI becoming mainstream in everyone’s life and complementing human capabilities to solve some of the problems that have troubled us for a long time. This book takes a holistic approach into the theory of machine learning and AI, starting from the very basics to building applications with cognitive intelligence. We have taken a simple approach to illustrate the core concepts and theory, supplemented by illustrative diagrams and examples.

It will be encouraging for us for readers to benefit from the book and fast-track their learning and innovation into one of the most exciting fields of computing so they can create a truly intelligent system that will augment our abilities to the next level.