Grokking Data Structures

📚📚 I. THÔNG TIN SẢN PHẨM
📒 Mã sản phẩm :  STT1133
📒 Nhà xuất bản : Manning (August 13, 2024)
📒 Tác giả : Marcello La Rocca
📒 Ngôn ngữ :   Tiếng Anh
📒 ISBN      : 1633436993
📒 Số trang :  280 trang
📒 Hình thức : Bìa Mềm, IN ĐEN TRẮNG
📒 Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
📒 Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và hightlight thoải mái.
📒 Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.

📚📚 II. MÔ TẢ SẢN PHẨM
📒 1.Mô tả sản phẩm

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.

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.

📒 2. Tác giả

Marcello La Rocca is a research scientist and a full-stack engineer. His focus is on optimization algorithms, genetic algorithms, machine learning, and quantum computing.