Language : English
Published : 2013-03-18
Pages : 748
Data Structures and Algorithms in Python
Based on the authors’ market leading data structures books in Java and C++, this book offers a comprehensive, definitive introduction to data structures in Python by authoritative authors. Data Structures and Algorithms in Python is the first authoritative object-oriented book available for Python data structures. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++. Begins by discussing Python’s conceptually simple syntax, which allows for a greater focus on concepts. Employs a consistent object-oriented viewpoint throughout the text. Presents each data structure using ADTs and their respective implementations and introduces important design patterns as a means to organize those implementations into classes, methods, and objects. Provides a thorough discussion on the analysis and design of fundamental data structures. Includes many helpful Python code examples, with source code provided on the website. Uses illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Provides hundreds of exercises that promote creativity, help readers learn how to think like programmers, and reinforce important concepts. Contains many Python-code and pseudo-code fragments, and hundreds of exercises, which are divided into roughly 40% reinforcement exercises, 40% creativity exercises, and 20% programming projects.
Research Methods for Business Students has been fully revised for this seventh edition and continues to be the market-leading textbook in its field, guiding hundreds of thousands of student researchers to success in their research methods modules, research proposals, projects and dissertations. So, if you’re thinking …’How do I choose my topic?’ ‘I’m confused by all these different philosophies’ ‘I need to collect my data; what do I do first?’ ‘When and what do I need to write? …then, open this book to discover: * Regular checklists and ‘Progressing your research project’ sections to give you step-by-step practical guidance on the process * A glossary of clear definitions for 600 research terms * Cases and examples of students’ and academics’ research and topical news articles illustrating research in practice * Detailed chapters on choosing your topic, reviewing the literature, understanding philosophies, research design, access and ethics, secondary data, data collection and analysis, and writing about and presenting your research Don’t forget to visit www.pearsoned.co.uk/saunders where you can use online tutorials on research software, such as IBM SPSS Statistics and NVivo, test yourself with hundreds of multiple choice questions, analyse over 60 further case studies, and learn how to search the Internet more efficiently and effectively with our Smarter Online Searching guide! Start your project with confidence and complete it with success! Mark Saunders is Professor of Business Research Methods at The Surrey Business School, University of Surrey. Philip Lewis was a Principal Lecturer and Adrian Thornhill was a Head of Department, both at the University of Gloucestershire.
About the Author
Aaron Podolefsky is Provost and Vice President for Academic at the University of Northern Iowa, where he also served eight years as Dean of the College of Social and Behavioral Sciences. He received his Ph.D. in Anthropology from the State University of New York at Stony Brook and also holds degrees in Liberal Studies and Mathematics. He has authored books on law in Papua New Guinea and crime prevention in urban America. Peter J. Brown is a Professor of Anthropology at Emory University, where he also holds a faculty position in the Rollins School of Public Health. He is currently director of Emory’s Center for the Study of Health, Culture and Society. He has served as an officer in the Society for Medical Anthropology and was Editor-in-Chief of the journal Medical Anthropology for nine years. He has done research on a variety of topics, including malaria, tuberculosis, obesity, Alzheimer’s disease, male gender and health, and the history of international health policy. He has been the recipient of three teaching awards. He has co-edited The Anthropology of Infectious Disease (with Marcia Inhorn) as well as the textbooks Applying Anthropology (sixth edition) and Applying Cultural Anthropology (fifth edition) (both with Aaron Podolefsky.
Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms. Quotes This book provides a comprehensive coverage of important data mining techniques. Numerous examples are provided to lucidly illustrate the key concepts. -Sanjay Ranka, University of Florida In my opinion this is currently the best data mining text book on the market. I like the comprehensive coverage which spans all major data mining techniques including classification, clustering, and pattern mining (association rules). -Mohammed Zaki, Rensselaer Polytechnic Institute