Hands-On Data Structures And Algorithms With Python
Hands-On Data Structures And Algorithms With Python ->>> https://urlin.us/2trjB5
Hands-On Data Structures And Algorithms With Python
Dr. Basant Agarwal works as an Assistant Professor at the Indian Institute of Information Technology Kota. He holds a PhD and MTech from the Department of Computer Science and Engineering, Malaviya National Institute of Technology, Jaipur, India. Basant has 10+ years of experience in academia and research, and he was awarded the prestigious PostDoc Fellowship by the European Research Consortium for Informatics and Mathematics through the Alain Bensoussan Fellowship Programme. He has been teaching a course on data structures and algorithms to undergraduates for a while now and is highly experienced in working with Python for developing real-world applications. His research interests include NLP, machine learning, and deep learning.
Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer.
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.
We just released a course on the freeCodeCamp YouTube channel that is a beginner-friendly introduction to common data structures (linked lists, stacks, queues, graphs) and algorithms (search, sorting, recursion, dynamic programming) in Python.
This book is for developers and programmers who are interested in learning about data structures and algorithms in Python to write complex, flexible programs. Basic Python programming knowledge is expected.
In this course you will learn data structures and algorithms by solving 80+ practice problems. You will begin each course by learning to solve defined problems related to a particular data structure and algorithm. By the end of each course, you would be able to evaluate and assess different data structures and algorithms for any open-ended problem and implement a solution based on your design choices.
Learn different data structures that can be used to store data. Implement different methods used to manipulate these data structures and examine the efficiency. Understand the advantages and applications of different data structures. Learn how to approach open ended problems (either in interview or real-world) and select appropriate data structures based on requirements.
Learn and implement basic algorithms such as searching and sorting on different data structures and examine the efficiency of these algorithms. Use recursion to implement these algorithms and then learn how some of these algorithms can be implemented without recursion. Practice selecting