SciPy Recipes
This is the code repository for SciPy Recipes, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.
About the Book
This book includes hands-on recipes for using the different components of the SciPy Stack such as NumPy, SciPy, matplotlib, and pandas, among others. You will use these libraries to solve real-world problems in linear algebra, numerical analysis, data visualization, and much more. The recipes included in the book will ensure you get a practical understanding not only of how a particular feature in SciPy Stack works, but also of its application to real-world problems. The independent nature of the recipes also ensure that you can pick up any one and learn about a particular feature of SciPy without reading through the other recipes, thus making the book a very handy and useful guide.
Instructions and Navigation
All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.
All chapters have codes, required support files can be found in the data folders within chapter folders where applicable.
The code will look like the following:
x = np.array([[1,2,3,4],
[5,6,7,8]])
y = np.repeat(x, [1,0,1,0], axis=1)
To get the most from this book, the reader needs to know the basics of Python; it's not necessary that the reader has the ability to program because the first chapter explains how to install the plugins needed to work with SciPy. The following are the software and OS requirements:
- SciPy 1.0.0
- NumPy v1.13
- Matplotlib 2.1.0
- Python 2.7, 3.5, and 3.6
- Python Data Analysis Library (v0.21.0)
- SymPy 1.1.1
- Released libraries
- OS required: Windows, Mac, or Linux
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Mastering Machine Learning with scikit-learn - Second Edition
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