Bibliographic Information

Algorithms

by John Paul Mueller and Luca Massaron

(--For dummies)

John Wiley & Sons, Inc., c2022

2nd ed.

  • : pbk

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Algorithms for dummies

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Includes index

Description and Table of Contents

Description

Your secret weapon to understanding-and using!-one of the most powerful influences in the world today From your Facebook News Feed to your most recent insurance premiums-even making toast!-algorithms play a role in virtually everything that happens in modern society and in your personal life. And while they can seem complicated from a distance, the reality is that, with a little help, anyone can understand-and even use-these powerful problem-solving tools! In Algorithms For Dummies, you'll discover the basics of algorithms, including what they are, how they work, where you can find them (spoiler alert: everywhere!), who invented the most important ones in use today (a Greek philosopher is involved), and how to create them yourself. You'll also find: Dozens of graphs and charts that help you understand the inner workings of algorithms Links to an online repository called GitHub for constant access to updated code Step-by-step instructions on how to use Google Colaboratory, a zero-setup coding environment that runs right from your browser Whether you're a curious internet user wondering how Google seems to always know the right answer to your question or a beginning computer science student looking for a head start on your next class, Algorithms For Dummies is the can't-miss resource you've been waiting for.

Table of Contents

Introduction 1 Part 1: Getting Started with Algorithms 7 Chapter 1: Introducing Algorithms 9 Chapter 2: Considering Algorithm Design 23 Chapter 3: Working with Google Colab 41 Chapter 4: Performing Essential Data Manipulations Using Python 59 Chapter 5: Developing a Matrix Computation Class 79 Part 2: Understanding the Need to Sort and Search 97 Chapter 6: Structuring Data 99 Chapter 7: Arranging and Searching Data 117 Part 3: Exploring the World of Graphs 139 Chapter 8: Understanding Graph Basics 141 Chapter 9: Reconnecting the Dots 161 Chapter 10: Discovering Graph Secrets 195 Chapter 11: Getting the Right Web page 207 Part 4: Wrangling Big Data 223 Chapter 12: Managing Big Data 225 Chapter 13: Parallelizing Operations 249 Chapter 14: Compressing and Concealing Data 267 Part 5: Challenging Difficult Problems 289 Chapter 15: Working with Greedy Algorithms 291 Chapter 16: Relying on Dynamic Programming 307 Chapter 17: Using Randomized Algorithms 331 Chapter 18: Performing Local Search 349 Chapter 19: Employing Linear Programming 367 Chapter 20: Considering Heuristics 381 Part 6: The Part of Tens 401 Chapter 21: Ten Algorithms That Are Changing the World 403 Chapter 22: Ten Algorithmic Problems Yet to Solve 411 Index 417 ntroduction 1 Part 1: Getting Started with Algorithms 7 Chapter 1: Introducing Algorithms 9 Chapter 2: Considering Algorithm Design 23 Chapter 3: Working with Google Colab 41 Chapter 4: Performing Essential Data Manipulations Using Python 59 Chapter 5: Developing a Matrix Computation Class 79 Part 2: Understanding the Need to Sort and Search 97 Chapter 6: Structuring Data 99 Chapter 7: Arranging and Searching Data 117 Part 3: Exploring the World of Graphs 139 Chapter 8: Understanding Graph Basics 141 Chapter 9: Reconnecting the Dots 161 Chapter 10: Discovering Graph Secrets 195 Chapter 11: Getting the Right Web page 207 Part 4: Wrangling Big Data 223 Chapter 12: Managing Big Data 225 Chapter 13: Parallelizing Operations 249 Chapter 14: Compressing and Concealing Data 267 Part 5: Challenging Difficult Problems 289 Chapter 15: Working with Greedy Algorithms 291 Chapter 16: Relying on Dynamic Programming 307 Chapter 17: Using Randomized Algorithms 331 Chapter 18: Performing Local Search 349 Chapter 19: Employing Linear Programming 367 Chapter 20: Considering Heuristics 381 Part 6: The Part of Tens 401 Chapter 21: Ten Algorithms That Are Changing the World 403 Chapter 22: Ten Algorithmic Problems Yet to Solve 411 Index 417 ntroduction 1 Part 1: Getting Started with Algorithms 7 Chapter 1: Introducing Algorithms 9 Chapter 2: Considering Algorithm Design 23 Chapter 3: Working with Google Colab 41 Chapter 4: Performing Essential Data Manipulations Using Python 59 Chapter 5: Developing a Matrix Computation Class 79 Part 2: Understanding the Need to Sort and Search 97 Chapter 6: Structuring Data 99 Chapter 7: Arranging and Searching Data 117 Part 3: Exploring the World of Graphs 139 Chapter 8: Understanding Graph Basics 141 Chapter 9: Reconnecting the Dots 161 Chapter 10: Discovering Graph Secrets 195 Chapter 11: Getting the Right Web page 207 Part 4: Wrangling Big Data 223 Chapter 12: Managing Big Data 225 Chapter 13: Parallelizing Operations 249 Chapter 14: Compressing and Concealing Data 267 Part 5: Challenging Difficult Problems 289 Chapter 15: Working with Greedy Algorithms 291 Chapter 16: Relying on Dynamic Programming 307 Chapter 17: Using Randomized Algorithms 331 Chapter 18: Performing Local Search 349 Chapter 19: Employing Linear Programming 367 Chapter 20: Considering Heuristics 381 Part 6: The Part of Tens 401 Chapter 21: Ten Algorithms That Are Changing the World 403 Chapter 22: Ten Algorithmic Problems Yet to Solve 411 Index 417

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