PDF Ebook Data Structures and Algorithms with Python (Undergraduate Topics in Computer Science), by Kent D. Lee, Steve Hubbard
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Data Structures and Algorithms with Python (Undergraduate Topics in Computer Science), by Kent D. Lee, Steve Hubbard
PDF Ebook Data Structures and Algorithms with Python (Undergraduate Topics in Computer Science), by Kent D. Lee, Steve Hubbard
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This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. Features: includes both introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses provided in the preface; provides learning goals, review questions and programming exercises in each chapter, as well as numerous illustrative examples; offers downloadable programs and supplementary files at an associated website, with instructor materials available from the author; presents a primer on Python for those from a different language background.
- Sales Rank: #747776 in Books
- Published on: 2015-01-15
- Released on: 2015-01-15
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .90" w x 6.10" l, 1.49 pounds
- Binding: Paperback
- 363 pages
From the Back Cover
This clearly structured and easy to read textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently.
Project-oriented and classroom-tested, the book presents a number of important algorithms supported by motivating examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. The text assumes some basic experience in computer programming and familiarity in an object-oriented language, but not necessarily with Python.
Topics and features:
- Includes both introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses provided in the preface
- Provides learning goals, review questions and programming exercises in each chapter, as well as numerous illustrative examples
- Offers downloadable programs and supplementary files at an associated website, with instructor materials available from the author
- Presents a primer on Python for those coming from a different language background
- Reviews the use of hashing in sets and maps, along with an examination of binary search trees and tree traversals, and material on depth first search of graphs
- Discusses topics suitable for an advanced course, such as membership structures, heaps, balanced binary search trees, B-trees and heuristic search
Students of computer science will find this clear and concise textbook to be invaluable for undergraduate courses on data structures and algorithms, at both introductory and advanced levels. The book is also suitable as a refresher guide for computer programmers starting new jobs working with Python.
About the Author
Dr. Kent D. Lee is Professor of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer textbook Python Programming Fundamentals and the forthcoming Foundations of Programming Languages.
Dr. Steve Hubbard is Professor of Mathematics and Computer Science at Luther College.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Exactly what I was looking for
By real san diego reader
I purchased this book to prep for technical interviews and it was just what I was looking for. Each topic is covered thoroughly and should serve well whether you're learning for the first time or just need a refresher (like me). The example code is clean and compact, and there are lots of colorful figures throughout. The book itself is also nice and compact, about the size of a large novel rather than a huge backbreaking textbook.
My only (very small) complaint is that the code doesn't follow the PEP 8 style guide.
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