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Full 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.
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
