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  • Book Overview & Buying Machine Learning For Dummies
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Machine Learning For Dummies

Machine Learning For Dummies

By : John Paul Mueller, Luca Massaron
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Machine Learning For Dummies

Machine Learning For Dummies

By: John Paul Mueller, Luca Massaron

Overview of this book

Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn’t be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks. In the initial chapters, the book introduces you to the world of machine learning, artificial intelligence, big data, and will prepare you to use R and Python for machine learning tasks. Next, you’ll learn how to use math in machine learning and get started with linear models and neural networks. In the final chapters, you’ll process images and text, and discover packages and techniques to improve your machine learning models. By the end of this book, you’ll be able to understand and implement machine learning seamlessly.
Table of Contents (34 chapters)
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2
Part 1: Introducing How Machines Learn
6
Part 2: Preparing Your Learning Tools
12
Part 3: Getting Started with the Math Basics
17
Part 4: Learning from Smart and Big Data
24
Part 5: Applying Learning to Real Problems
28
Part 6: The Part of Tens
31
About the Author
32
Advertisement Page
33
Connect with Dummies
34
End User License Agreement

Chapter 3

Having a Glance at the Future

IN THIS CHAPTER

Discovering how machine learning will help create useful future technologies

Developing new kinds of work as the result of machine learning

Considering how machine learning can create potential problems

Machine learning technology appears in many products today, but it isn’t even close to complete usability yet. The algorithms used for machine learning today are still relatively basic when compared to what scientists plan to provide for the future. In addition, the data sources for machine learning today are smaller than the datasets planned for future use. In short, machine learning is in its infancy. It already performs a considerable number of tasks amazingly well, however. This chapter looks at what might be possible in the future. It helps you understand the direction that machine learning is taking and how that direction could help entrench machine learning into every aspect of daily life.

One of the issues that comes...

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83
Tech Concepts
36
Programming languages
73
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Machine Learning For Dummies
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