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Training Systems Using Python Statistical Modeling

You're reading from   Training Systems Using Python Statistical Modeling Explore popular techniques for modeling your data in Python

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781838823733
Length 290 pages
Edition 1st Edition
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Author (1):
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Curtis Miller Curtis Miller
Author Profile Icon Curtis Miller
Curtis Miller
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Toc

To get the most out of this book

You will need Anaconda and Jupyter Notebook. You also need to be familiar with Python, and various machine learning libraries such as NumPy and pandas.

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at www.packt.com.
  2. Select the SUPPORT tab.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR/7-Zip for Windows
  • Zipeg/iZip/UnRarX for Mac
  • 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Training-Your-Systems-with-Python-Statistical-Modeling. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "As seen here, the iris dataset comes with sepal length, sepal width, petal length, and petal width."

Any command-line input or output is written as follows:

$ jupyter notebook
Warnings or important notes appear like this.
Tips and tricks appear like this.
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