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

<p><b> John Mueller</b> 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.</p> <p><b>Luca Massaron</b> 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.

<p><b>Feel the algorithm and join the data dance </b></p> <p>Algorithms are everywhere—in your web browser, your music app, the grocery store checkout, and possibly even in your car. <i>Algorithms For Dummies</i> 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. <p><b>Inside…</b> <ul><b><li>Create algorithms the easy way with the Python^® language</li> <li>Practical real-world algorithm uses</li> <li>Approaches to solving difficult problems</li> <li>Online access to code</li> <li>World-famous algorithms</li> <li>Tips on working with big data</li> <li>Discover practical algorithm history</li></b></ul>

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