Book Image

Hands-On Data Structures and Algorithms with Python - Second Edition

By : Dr. Basant Agarwal, Benjamin Baka
Book Image

Hands-On Data Structures and Algorithms with Python - Second Edition

By: Dr. Basant Agarwal, Benjamin Baka

Overview of this book

Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.
Table of Contents (16 chapters)

Implementations, Applications, and Tools

Learning about algorithms without any real-life application remains a purely academic pursuit. In this chapter, we will explore the data structures and algorithms that are shaping our world.

One of the golden nuggets of this age is the abundance of data. Emails, phone numbers, text documents, and images contain large amounts of data. In this data, there is valuable information that makes the data more important. But to extract this information from the raw data, we have to use data structures, processes, and algorithms that specialize in this task.

Machine learning employs a significant number of algorithms to analyze and predict the occurrence of certain variables. Analyzing data on a purely numerical basis still leaves much of the latent information buried in the raw data. Presenting data visually thus enables one to understand and gain...