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Matplotlib 3.0 Cookbook

You're reading from  Matplotlib 3.0 Cookbook

Product type Book
Published in Oct 2018
Publisher Packt
ISBN-13 9781789135718
Pages 676 pages
Edition 1st Edition
Languages
Authors (2):
Srinivasa Rao Poladi Srinivasa Rao Poladi
Profile icon Srinivasa Rao Poladi
Nikhil Borkar Nikhil Borkar
Profile icon Nikhil Borkar
View More author details

Table of Contents (17) Chapters

Preface 1. Anatomy of Matplotlib 2. Getting Started with Basic Plots 3. Plotting Multiple Charts, Subplots, and Figures 4. Developing Visualizations for Publishing Quality 5. Plotting with Object-Oriented API 6. Plotting with Advanced Features 7. Embedding Text and Expressions 8. Saving the Figure in Different Formats 9. Developing Interactive Plots 10. Embedding Plots in a Graphical User Interface 11. Plotting 3D Graphs Using the mplot3d Toolkit 12. Using the axisartist Toolkit 13. Using the axes_grid1 Toolkit 14. Plotting Geographical Maps Using Cartopy Toolkit 15. Exploratory Data Analysis Using the Seaborn Toolkit 16. Other Books You May Enjoy

Contour plot

The contour plot is typically used to display how the error varies with varying coefficients that are being optimized in a machine learning algorithm, such as linear regression. If the linear regression coefficients are theta0 and theta1, and the error between the predicted value and the actual value is a Loss, then for a given Loss value, all the values of theta0 and theta1 form a contour. For different values of Loss, different contours are formed by varying the values of theta0 and theta1.

Getting ready

The data for Loss, theta0, theta1, and theta (optimal values of theta0 and theta1 that give the lowest error) are taken from one of the regression problems for plotting the contour plot. If theta0 and theta1...

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