Pocket Primer Series Read Description

Python Data Structures Pocket Primer

Paperback
December 2022
9781683927570
More details
  • Publisher
    Mercury Learning and Information
  • Published
    6th December 2022
  • ISBN 9781683927570
  • Language English
  • Pages 229 pp.
  • Size 6" x 9"
$39.95
E-Book

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December 2022
9781683927556
More details
  • Publisher
    Mercury Learning and Information
  • Published
    6th December 2022
  • ISBN 9781683927556
  • Language English
  • Pages 229 pp.
  • Size 6" x 9"
$34.95
Lib E-Book

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December 2022
9781683927563
More details
  • Publisher
    Mercury Learning and Information
  • Published
    6th December 2022
  • ISBN 9781683927563
  • Language English
  • Pages 229 pp.
  • Size 6" x 9"
$109.95

As part of the best-selling Pocket Primer series, this book is designed to present the fundamentals of data structures using Python. Data structures provide a means to manage huge amounts of information such as large databases and the ability to use search and sort algorithms effectively. It is intended to be a fast-paced introduction to the core concepts of Python and data structures, illustrated with numerous code samples. Companion files with source code are available for downloading.

FEATURES:

  • Begins with an introduction to Python, and covers recursion, strings, search and sort, linked lists, stacks, and more
  • Features numerous code samples throughout
  • Includes companion files with source code available for downloading.

1: Introduction to Python
2: Recursion and Combinatorics
3: Strings and Arrays
4: Search and Sort Algorithms
5: Linked Lists
6: Linked Lists and Common Tasks
7: Queues and Stacks
Index

Oswald Campesato

Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).

Computer Science; Programming; Python; Data Science; neural networks; data processing