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9.5 MB
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8756BB0D2B1CA626A39CC0A87D765C46D5CE6C59
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Oct. 27, 2025, 9:29 a.m.
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(Last updated: Oct. 27, 2025, 9:30 a.m.)
| File | Size |
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| Mueller J., Massaron L. Machine Learning For Dummies 3ed 2026.pdf | 9.5 MB |
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12.6 MB
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2023-07-01
| Uploaded by indexFroggy | Size 12.6 MB | Health [ 13 /1 ] | Added 2023-07-01 |
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SOURCE: Mueller J., Massaron L. Machine Learning For Dummies 3ed 2026
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MEDIAINFO
Textbook in PDF format The most human-friendly book on Machine Learning. Somewhere buried in all the systems that drive Artificial Intelligence (AI), you'll find Machine Learning—the process that allows technology to build knowledge based on data and patterns. Machine Learning For Dummies is an excellent starting point for anyone who wants deeper insight into how all this learning actually happens. This book offers an overview of Machine Learning (ML) and its most important practical applications. Then, you'll dive into the tools, code, and math that make Machine Learning go—and you'll even get step-by-step instructions for testing it out on your own. For an easy-to-follow introduction to building smart algorithms, this Dummies guide is your go-to. • Piece together what Machine Learning is, what it can do, and what it can't do • Learn the basics of Machine Learning code and how it integrates with large datasets • Understand the mathematical principles that AI uses to make itself smarter • Consider real-world applications of Machine Learning and write your own algorithms Machines and humans learn in entirely different ways, which is why the first part of this book is essential to your understanding of Machine Learning. Machines perform routine tasks at incredible speeds, but still require human oversight on many aspects, from how they learn to how they execute their tasks. This book will help you understand how to guide these machines to solve problems that traditionally required human thought. The second part of this book focuses on utilizing the various Python coding examples on your computer by explaining how to access Google Colab and the example data encountered in the chapters, and using them to learn more from this book. The third part of the book discusses basic math concepts in relation to Machine Learning requirements. It prepares you to perform math tasks associated with algorithms used in Machine Learning to make predictions from your data, such as forecasting a value (regression) or determining a category (classification). The fourth part of the book helps you discover what to do about data that isn’t quite up to par. This part is also where you start learning about similarity and working with linear models. The most advanced chapter tells you how to work with ensembles of learners to perform tasks that might not otherwise be reasonable to complete. The fifth part of the book is about the practical application of Machine Learning techniques. You’ll learn how to perform tasks such as classifying images, analyzing opinions and sentiments, and recommending products and movies, all using Machine Learning. The last part of the book contains helpful information to enhance your Machine Learning experience. With clear explanations and hands-on instruction, Machine Learning For Dummies is a great entry-level resource for developers looking to get started with AI and Machine Learning. Preface Introduction Introducing How Machines Learn Learning Machine Learning by Coding Working with Google Colab Understanding the Tools of the Trade Getting Beyond Basic Coding in Python Building the Foundations Learning from Smart Algorithms Applying Learning to Real Problems The Part of Tens
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