Читать книгу Machine Learning For Dummies - John Paul Mueller, John Mueller Paul, Luca Massaron - Страница 28

IN THIS CHAPTER

Understanding and locating big data

Considering how statistics and big data work together in machine learning

Defining the role of algorithms in machine learning

Determining how training works with algorithms in machine learning

This chapter provides you with essentials you need to know to perform machine learning tasks. This chapter doesn’t go into detail on the topics; rather, it offers an overview to help you make sense of the information in future chapters. Of course, learning begins with data, so the first part of this chapter tells you about data — lots of data, big data. Just as a human learns better with more input, so do machine learning applications.

You have to have some way to organize and analyze all that data. Just as you organize pieces of information to make them easier to access and see patterns in it with greater ease, so the computer needs to organize data and then analyze it using statistics —a method of interpreting and presenting data patterns mathematically. The second part of this chapter deals with statistics as they apply to machine learning.

After you have your data in hand and in an order that is useful and understandable, you can begin to feed it to algorithms to manipulate the data in a particular way to produce a result. The result tells you something you may or may not have surmised about the data on your own. The third part of this chapter looks at the relationship of algorithms to machine learning.

Machine learning algorithms are useful only when trained because training enables the computer to use previous analysis to work with new data that it hasn’t seen before. The fourth part of this chapter gets you started with understanding algorithm training.