Algorithms & Data Structures in Python - Softcover

Jagannathan, Srinivasan; Sinenian, Nareg

 
9781502378712: Algorithms & Data Structures in Python

Synopsis

This book covers a wide breadth of important and useful subject matter without sacrificing depth. It introduces the reader to the Python programming language, but does not assume deep prior knowledge of computer science or computer programming. The book also provides an in-depth introduction to a variety of algorithms and data structures that are used throughout the industry. In addition, it introduces the reader to important basic concepts in computer science, networking, cryptography, numerical analysis, and computational geometry. The authors provide many illustrative examples written in Python. Python source code of examples used throughout the book can be obtained from: https://github.com/pythonbook/pythonbook

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From the Back Cover

This book covers a wide breadth of important and useful subject matter without sacrificing depth. It introduces the reader to the Python programming language, but does not assume deep prior knowledge of computer science or computer programming. The book also provides an in-depth introduction to a variety of algorithms and data structures that are used throughout the industry. In addition, it introduces the reader to important basic concepts in computer science, networking, cryptography, numerical analysis, and computational geometry. The authors provide many illustrative examples written in Python. I recommend this book for anyone who wants to make a serious, deep dive into the implementation of a wide variety of algorithms and data structures in the Python programming language.
- David M. Cummings, Ph.D.

Algorithms & Data Structures in Python is a valuable text for students in introductory computer science courses, or for scientists and engineers to add computational methods to their repertoire. Python is a good choice for readers at this level due to its wide use and continually gaining popularity in curricula and scientific/engineering applications. The chapters on algorithms and data structures provide an excellent foundation for the student, and scientists learning computational techniques will go further through the later chapters on numerical methods, simulation techniques, and computational geometry.
- Alex B. Zylstra

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