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Hands-On Data Structures and Algorithms with Python

Hands-On Data Structures and Algorithms with Python

By : Dr. Basant Agarwal, Benjamin Baka
3 (13)
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Hands-On Data Structures and Algorithms with Python

Hands-On Data Structures and Algorithms with Python

3 (13)
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)
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Learning about machine learning

Machine learning is a subfield of artificial intelligence. Machine learning is basically an algorithm that can learn from the example data and can provide predictions based on that. Machine learning models learn the patterns from the data examples and use those learned patterns to make predictions for unseen data. For example, we feed many examples of spam and ham email messages to develop a machine learning model that can learn the patterns in emails and can classify new emails as spam or ham.

Types of machine learning

There are three broad categories of machine learning, as follows:

  • Supervised learning: Here, an algorithm is fed a set of inputs and their corresponding outputs. The algorithm...
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