Peeling Data Structures and Algorithms:
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 GoLang 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 Go" is designed to give a jump-start to programmers, job hunters, and those who are appearing for exams. All the code in this book is written in GoLang. It contains many programming puzzles that not only encourage analytical thinking but also prepare 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
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Specifications
Book Details
Imprint
Careermonk Publications
Publication Year
2020
Contributors
Author Info
Narasimha Karumanchi is the founder of CareerMonk Publications and author of few books on data structures, algorithms, and design patterns. He was a software developer who has been both interviewer and interviewee over his long career. Most recently he worked for Amazon Corporation, IBM Software Labs, and Microsoft. Narasimha holds M.Tech. in computer science from IIT, Bombay, and B.Tech. from JNT University. He authored the following books which got translated to international: China, Japan, Korea, and Taiwan. Also, around 58 international universities were using these books as references for academic courses.
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