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Numerical Computing with Python

You're reading from Numerical Computing with Python Harness the power of Python to analyze and find hidden patterns in the data

Product type Course

Published in Dec 2018

Publisher Packt

ISBN-13 9781789953633

Length 682 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Data Mining

Authors (5):

Pratap Dangeti

Theodore Petrou

Allen Yu

Aldrin Yim

Claire Chung

+1 more

View More author details

Table of Contents (21) Chapters

Title Page

Contributors

About Packt

Preface

1. Journey from Statistics to Machine Learning FREE CHAPTER

2. Tree-Based Machine Learning Models

3. K-Nearest Neighbors and Naive Bayes

4. Unsupervised Learning

5. Reinforcement Learning

6. Hello Plotting World!

7. Visualizing Online Data

8. Visualizing Multivariate Data

9. Adding Interactivity and Animating Plots

10. Selecting Subsets of Data

11. Boolean Indexing

12. Index Alignment

13. Grouping for Aggregation, Filtration, and Transformation

14. Restructuring Data into a Tidy Form

15. Combining Pandas Objects

1. Other Books You May Enjoy

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Index

Non-interactive backends

The code for plotting graphs is considered the frontend in Matplotlib terminology. We first mentioned backends in Chapter 6, Hello Plotting World!, when we were talking about output formats. In reality, Matplotlib backends differ much more than just in the support of graphical formats. Backends handle so many things behind the scenes! And that determines the support for plotting capabilities. For example, LaTeX text layout is only supported by AGG, PDF, PGF, and PS backends.

We have been using non-interactive backends so far, which include AGG, Cairo, GDK, PDF, PGF, PS, and SVG. Most of these backends work without extra dependencies, yet Cairo and GDK would require the Cairo graphics library or GIMP Drawing Kit, respectively, to work.

Non-interactive backends can be further classified into two groups--vector and raster. Vector graphics describe images in terms of points, paths, and shapes that are calculated using mathematical formulas. A vector graphic will always...

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Authors (5)

Pratap Dangeti

Pratap Dangeti

Pratap Dangeti develops machine learning and deep learning solutions for structured, image, and text data at TCS, analytics and insights, innovation lab in Bangalore. He has acquired a lot of experience in both analytics and data science. He received his master's degree from IIT Bombay in its industrial engineering and operations research program. He is an artificial intelligence enthusiast. When not working, he likes to read about next-gen technologies and innovative methodologies.

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Aldrin Yim

Aldrin Yim

Aldrin Yim is a PhD candidate and Markey Scholar in the Computation and System Biology program at Washington University, School of Medicine. His research focuses on applying big data analytics and machine learning approaches in studying neurological diseases and cancer. He is also the founding CEO of Codex Genetics Limited, which provides precision medicine solutions to patients and hospitals in Asia.

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Claire Chung

Claire Chung

Claire Chung is pursuing her PhD degree as a Bioinformatician at the Chinese University of Hong Kong. She enjoys using Python daily for work and lifehack. While passionate in science, her challenge-loving character motivates her to go beyond data analytics. She has participated in web development projects, as well as developed skills in graphic design and multilingual translation. She led the Campus Network Support Team in college, and shared her experience in data visualization in PyCon HK 2017.

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Allen Yu

Allen Yu

Allen Yu, PhD, is a Chevening Scholar, 2017-18, and an MSC student in computer science at the University of Oxford. He holds a PhD degree in Biochemistry from the Chinese University of Hong Kong, and he has used Python and Matplotlib extensively during his 10 years of bioinformatics experience. Apart from academic research, Allen is the co-founder of Codex Genetics Limited, which aims to provide a personalized medicine service in Asia through the use of the latest genomics technology.

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Theodore Petrou

Theodore Petrou

Theodore Petrou is the founder of Dunder Data, a training company dedicated to helping teach the Python data science ecosystem effectively to individuals and corporations. Read his tutorials and attempt his data science challenges at the Dunder Data website.

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