"Provides an introduction to the fundamental principles of data science, walking the reader through the "data-analytic thinking" necessary for extracting useful knowledge and business value from collected data."
"This book brings educator up-to-date on the current state of the field. Teachers who use this book should be able to think about new teaching strategies to help students develop better self-regulation and to learn effectively."
"The star atlas companion is the ideal companion to any star atlas, as it is the first book to provide a true perspective on the characteristics and distances of over 1,100 stars and their movement through space. With the aid of scale diagrams, the reader can grasp difficult-to-understand concepts such as how far apart stars really are, their relative sizes, how fast they spin and their shapes, and how the constellation patterns change over time. This book, describes many stars visible to the naked eye in both the northern and southern hemispheres, explains binary and multiple star systems in detail, gives the properties of many open clusters, enables a true appreciation of the scale of our galactic neighborhood."
"This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the "dangerous" uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the "2010 National Excellent Doctoral Dissertation Award", the highest honor for not more than 100 PhD theses per year in China."
