Dawn Holmes is a faculty member in the Department of Statistics and Applied Probability at the University of California, Santa Barbara, specializing in Bayesian networks, machine learning, and data mining. She is the co-editor of a three-volume work, Data Mining: Foundations and Intelligent Paradigms (Springer, 2014), and Associate Editor of the International Journal of Knowledge-Based and Intelligent Information Systems.
Big data is in the news, and this excellent very short introduction brings the reader up to speed and enables them to understand the various components and implications. * Paradigm Explorer * This is a very useful, concise introduction to the topic of big data. * Jonathan Cowie, Science Fact & Science Fiction Concatenation * A very short introduction to a very big subject ... arguably the most topical of this book series ... This very short introduction is perfect for anyone who is a little bit baffled by the very concept of big data. Holmes introduces the subject in a format that is both concise and manageable. * Jade Taylor-Salazar, E&T Magazine *