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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Getting Datasets

Often, one of the challenges in machine learning is obtaining sample datasets for experimentation. In machine learning, when you are just getting started with an algorithm, it is often useful to get started with a simple dataset that you can create yourself to test that the algorithm is working correctly according to your understanding. Once you clear this stage, it is time to work with a large dataset, and for this you would need to find the relevant source so that your machine learning model can be as realistic as possible.

Here are some places where you can get the sample dataset to practice your machine learning:

  • Scikit‐learn's built‐in dataset
  • Kaggle dataset
  • UCI (University of California, Irvine) Machine Learning Repository

Let's take a look at each of these in the following sections.

Using the Scikit‐learn Dataset

Scikit‐learn comes with a few standard sample datasets, which makes learning machine learning easy. To load the...