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Hands-On Data Science with Anaconda, published by Packt

License: MIT License

Python 24.37% Julia 2.81% R 12.38% Rebol 0.99% MATLAB 3.08% Jupyter Notebook 56.37%

hands-on-data-science-with-anaconda's Introduction

Hands-On Data Science with Anaconda

This is the code repository for Hands-On Data Science with Anaconda, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.

About the Book

The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod.

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 contains code.

The code will look like the following:

import matplotlib.pyplot as plt  
plt.plot([2,3,8,12]) 
plt.show() 

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Errata

Chapter 3, page 52:

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