The Data Science Design Manual (Texts in Computer Science)

This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. Additional learning tools:Contains “War Stories,” offering perspectives on how data science applies in the real worldIncludes “Homework Problems,” providing a wide range of exercises and projects for self-studyProvides a complete set of lecture slides and online video lectures at data-manualProvides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapterRecommends exciting “Kaggle Challenges” from the online platform KaggleHighlights “False Starts,”

Steven S. Skiena is Distinguished Teaching Professor of Computer Science at Stony Brook University, with research interests in data science, natural language processing, and algorithms. Skiena is the author of six books, including the popular Springer titles The Algorithm Design Manual and Programming Challenges: The Programming Contest Training Manual.. He was awarded the IEEE Computer Science and Engineering Undergraduate

Skiena is Distinguished Teaching Professor of Computer Science at Stony Brook University, with research interests in data science, natural language processing, and algorithms. He was awarded the IEEE Computer Science and Engineering Undergraduate Teaching Award “for outstanding contributions to undergraduate education and for influential textbooks and software.”  Dr. Skiena is the author of six books, including the popular Springer titles The Algorithm Design Manual and Programming Challenges: The Programming Contest Training Manual.. About t