Language
  • Python 2
Reading time
  • Approximately 49 days
What you will learn
  • Algorithm and Data Structure
Author
  • Narasimha Karumanchi
Published
  • 4 years, 8 months ago
Book cover of Data Structure and Algorithmic Thinking with Python: Data Structure and Algorithmic Puzzles by Narasimha Karumanchi

Official description

 Peeling Data Structures and Algorithms [re-printed on 21-January-2016]: Table of Contents: goo.gl/VLEUca Sample Chapter: goo.gl/8AEcYk Source Code: goo.gl/L8Xxdt Errata: goo.gl/EVftls Found issue? goo.gl/forms/uLXGYpyuzX Videos: goo.gl/BcHq74
The sample chapter should give you a very good idea of the quality and style of our book. In particular, be sure you are comfortable with the level and with our Python coding style. This book focuses on giving solutions for complex problems in data structures and algorithm. It even provides multiple solutions for a single problem, thus familiarizing readers with different possible approaches to the same problem. 
"Data Structure and Algorithmic Thinking with Python" is designed to give a jump-start to programmers, job hunters and those who are appearing for exams. All the code in this book are written in Python. It contains many programming puzzles that not only encourage analytical thinking, but also prepares readers for interviews. This book, with its focused and practical approach, can help readers quickly pick up the concepts and techniques for developing efficient and effective solutions to problems.
Topics Covered:
  • Organization of chapters
  • Introduction
  • Recursion and Backtracking
  • Linked Lists
  • Stacks
  • Queues
  • Trees
  • Priority Queue and Heaps
  • Disjoint Sets ADT
  • Graph Algorithms
  • Sorting   
  • Searching   
  • Selection Algorithms [Medians]   
  • Symbol Tables   
  • Hashing   
  • String Algorithms   
  • Algorithms Design Techniques   
  • Greedy Algorithms   
  • Divide and Conquer Algorithms   
  • Dynamic Programming   
  • Complexity Classes   
  • Miscellaneous Concepts   

Reviews

Write a review

Read this book? Comment on this book's GitHub issue page and share what you liked and what you didn't like about it. Your GitHub comment will show up as a review here. See an example.