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Details for:
La Rocca M. Grokking Data Structures 2024
la rocca m grokking data structures 2024
Type:
E-books
Files:
2
Size:
17.4 MB
Uploaded On:
July 7, 2024, 6:53 a.m.
Added By:
andryold1
Seeders:
1
Leechers:
1
Info Hash:
E2D1E7463821DE63C2FE3C58FCBBB447F363D3A7
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Textbook in PDF format Don't be perplexed by data structures! This fun, friendly, and fully illustrated guide makes it easy to learn useful data structures you'll put to work every day. Grokking Data Structures makes it a breeze to learn the most useful day-to-day data structures. You'll follow a steady learning path from absolute basics to advanced concepts, all illustrated with fun examples, engaging industry stories, and hundreds of graphics and cartoons. This book teaches data structures to anyone, no matter what their background. You don’t need advanced math, you don’t need to have taken CS101 or any course; you don’t need to be a coding ninja, but some knowledge of Python might help. This book, like every book in the Grooking series, gives you an understanding of how things work: what data structure is, what the basic structures you can use are, and how can you objectively decide which data structure is better for your task. It’s a book for beginners, meaning that it assumes no previous knowledge and it leverages your intuition and visual memory, but even if you are familiar with the subject, you might find it useful to dust off and even get a deeper understanding of some of the topics. In Grokking Data Structures you'll learn how to: Understand the most important and widely used data structures Identify use cases where data structures make the biggest difference Pick the best data structure solution for a coding challenge Understand the tradeoffs of data structures and avoid catastrophes Implement basic data collections like arrays, linked lists, stacks, and priority queues Use trees and binary search trees (BSTs) to organize data Use graphs to model relationships and learn about complex data Efficiently search by key using hash tables and hashing functions Reason about time and memory requirements of operations on data structures Grokking Data Structures carefully guides you from the most basic data structures like arrays or linked lists all the way to powerful structures like graphs. It's perfect for beginners, and you won't need anything more than high school math to get started. Each data structure you encounter comes with its own complete Python implementation so you can start experimenting with what you learn right away. Foreword by Daniel Zingaro. About the technology: Data structures are vital for shaping and handling your data organization. They're also an important part of most IT job interviews! Whether you're new to data structures or just dusting off what you learned in school, this book will get you up to speed fast with no advanced math, abstract theory, or complicated proofs. About the book: Grokking Data Structures introduces common and useful data structures that every developer needs to know. Real-world examples show you how data structures are used in practice, from making your searches faster to handling triage in an emergency room. You'll love the fun cartoons, insightful stories, and useful Python code samples that make data structures come alive. And unlike jargon-laden academic texts, this book is easy-to-read and practical. What's inside: Fast searches using hash tables Trees and binary search trees (BSTs) to organize data Use graphs to model complex data The best data structures for a coding challenge About the reader: For readers who know the basics of Python. A perfect companion to Grokking Algorithms! About the author: Marcello La Rocca is a research scientist and a full-stack engineer. He has contributed to large-scale web applications and machine learning infrastructure at Twitter, Microsoft, and Apple. Introducing data structures: Why you should learn about data structures Static arrays: Building your first data structure Sorted arrays: Searching faster, at a price Big-O notation: A framework for measuring algorithm efficiency Dynamic arrays: Handling dynamically sized datasets Linked lists: A flexible dynamic collection Abstract data types: Designing the simplest container—the bag Stacks: Piling up data before processing it Queues: Keeping information
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