Book Image

Python Machine Learning (Wiley)

By : Wei-Meng Lee
Book Image

Python Machine Learning (Wiley)

By: Wei-Meng Lee

Overview of this book

With computing power increasing exponentially and costs decreasing at the same time, this is the best time to learn machine learning using Python. Machine learning tasks that once required enormous processing power are now possible on desktop machines. Python Machine Learning begins by covering some fundamental libraries used in Python that make machine learning possible. You'll learn how to manipulate arrays of numbers with NumPy and use pandas to deal with tabular data. Once you have a firm foundation in the basics, you'll explore machine learning using Python and the scikit-learn libraries. You'll learn how to visualize data by plotting different types of charts and graphs using the matplotlib library. You'll gain a solid understanding of how the various machine learning algorithms work behind the scenes. The later chapters explore the common machine learning algorithms, such as regression, clustering, and classification, and discuss how to deploy the models that you have built, so that they can be used by client applications running on mobile and desktop devices. By the end of the book, you'll have all the knowledge you need to begin machine learning using Python.
Table of Contents (16 chapters)
Free Chapter
CHAPTER 9: Supervised Learning—Classification Using K‐Nearest Neighbors (KNN)
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Introduction to Scikit‐learn

In Chapters 24, you learned how to use Python together with libraries such as NumPy and Pandas to perform number crunching, data visualization, and analysis. For machine learning, you can also use these libraries to build your own learning models. However, doing so would require you to have a strong appreciation of the mathematical foundation for the various machine learning algorithms—not a trivial matter.

Instead of implementing the various machine learning algorithms manually by hand, fortunately, someone else has already done the hard work for you. Introducing Scikit‐learn, a Python library that implements the various types of machine learning algorithms, such as classification, regression, clustering, decision tree, and more. Using Scikit‐learn, implementing machine learning is now simply a matter of calling a function with the appropriate data so that you can fit and train the model.

In this chapter, first you will...