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Python Machine Learning (Wiley)

You're reading from   Python Machine Learning (Wiley) Python makes machine learning easy for beginners and experienced developers

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Product type Book
Published in Apr 2019
Publisher Wiley
ISBN-13 9781119545637
Pages 320 pages
Edition 1st Edition
Languages
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Author (1):
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Wei-Meng Lee Wei-Meng Lee
Author Profile Icon Wei-Meng Lee
Wei-Meng Lee
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Table of Contents (16) Chapters Close

1. Cover FREE CHAPTER
2. Introduction
3. CHAPTER 1: Introduction to Machine Learning 4. CHAPTER 2: Extending Python Using NumPy 5. CHAPTER 3: Manipulating Tabular Data Using Pandas 6. CHAPTER 4: Data Visualization Using matplotlib 7. CHAPTER 5: Getting Started with Scikit‐learn for Machine Learning 8. CHAPTER 6: Supervised Learning—Linear Regression 9. CHAPTER 7: Supervised Learning—Classification Using Logistic Regression 10. CHAPTER 8: Supervised Learning—Classification Using Support Vector Machines 11. CHAPTER 9: Supervised Learning—Classification Using K‐Nearest Neighbors (KNN) 12. CHAPTER 10: Unsupervised Learning—Clustering Using K‐Means 13. CHAPTER 11: Using Azure Machine Learning Studio 14. CHAPTER 12: Deploying Machine Learning Models 15. Index
16. End User License Agreement

Plotting Using Seaborn

While matplotlib allows you to plot a lot of interesting charts, it takes a bit of effort to get the chart that you want. This is especially true if you are dealing with a large amount of data and would like to examine the relationships between multiple variables.

Introducing Seaborn, a complementary plotting library that is based on the matplotlib data visualization library. Seaborn's strength lies in its ability to make statistical graphics in Python, and it is closely integrated with the Pandas data structure (covered in Chapter 3). Seaborn provides high‐level abstractions to allow you to build complex visualizations for your data easily. In short, you write less code with Seaborn than with matplotlib, while at the same time you get more sophisticated charts.

Displaying Categorical Plots

The first example that you will plot is called a categorical plot (formerly known as a factorplot). It is useful in cases when you want to plot the distribution...

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