Produktdetaljer
Biografisk notat
John Mueller has published more than 100 books on technology, data, and programming. John has a website and blog where he writes articles on technology and offers assistance alongside his published books.
Luca Massaron is a data scientist specializing in insurance and finance. A Google Developer Expert in machine learning, he has been involved in quantitative analysis and algorithms since 2000.
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.
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
Feel the algorithm and join the data dance
Algorithms are everywhere—in your web browser, your music app, the grocery store checkout, and possibly even in your car. Algorithms For Dummies will show you what they’re doing and how you can do it, too. You’ll learn to manipulate and structure data, build graphs using Python® programming language, and use basic programming techniques to make your algorithms run more smoothly. You might not be able to write an algorithm for a self-driving car or for a virtual assistant…but then again, maybe you will, with the solid foundation you’ll build in this book.
Inside…
- Create algorithms the easy way with the Python® language
- Practical real-world algorithm uses
- Approaches to solving difficult problems
- Online access to code
- World-famous algorithms
- Tips on working with big data
- Discover practical algorithm history
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.
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
Feel the algorithm and join the data dance
Algorithms are everywhere—in your web browser, your music app, the grocery store checkout, and possibly even in your car. Algorithms For Dummies will show you what they’re doing and how you can do it, too. You’ll learn to manipulate and structure data, build graphs using Python® programming language, and use basic programming techniques to make your algorithms run more smoothly. You might not be able to write an algorithm for a self-driving car or for a virtual assistant…but then again, maybe you will, with the solid foundation you’ll build in this book.
Inside…
- Create algorithms the easy way with the Python® language
- Practical real-world algorithm uses
- Approaches to solving difficult problems
- Online access to code
- World-famous algorithms
- Tips on working with big data
- Discover practical algorithm history
Produktdetaljer
Biografisk notat
John Mueller has published more than 100 books on technology, data, and programming. John has a website and blog where he writes articles on technology and offers assistance alongside his published books.
Luca Massaron is a data scientist specializing in insurance and finance. A Google Developer Expert in machine learning, he has been involved in quantitative analysis and algorithms since 2000.