https://github.com/PacktPublishing/Practical-Data-Science-Cookbook-Second-Edition
Practical Data Science Cookbook, Second Edition, published by Packt
https://github.com/PacktPublishing/Practical-Data-Science-Cookbook-Second-Edition
Last synced: 13 days ago
JSON representation
Practical Data Science Cookbook, Second Edition, published by Packt
- Host: GitHub
- URL: https://github.com/PacktPublishing/Practical-Data-Science-Cookbook-Second-Edition
- Owner: PacktPublishing
- License: mit
- Created: 2017-06-29T05:52:44.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2023-01-30T08:49:13.000Z (almost 3 years ago)
- Last Synced: 2024-05-13T00:44:10.724Z (over 1 year ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 52.7 MB
- Stars: 37
- Watchers: 7
- Forks: 40
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- machine-learning-resources - Practical Data Science Cookbook
README
# Practical Data Science Cookbook - Second Edition
This is the code repository for [Practical Data Science Cookbook - Second Edition](https://www.packtpub.com/big-data-and-business-intelligence/practical-data-science-cookbook-second-edition?utm_source=github&utm_medium=repository&utm_campaign=9781787129627), published by [Packt](https://www.packtpub.com/?utm_source=github). It contains all the supporting project files necessary to work through the book from start to finish.
## About the Book
As an increasing amount of data is generated each year, the need to analyze and operationalize it is more important than ever. Companies that know what to do with their data have a competitive advantage over companies that don't, and this drives a higher demand for knowledgeable and competent data professionals.
Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python.
## 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.
A block of code is set as follows:
```
```
Any command-line input or output is written as follows:
```
mysql -u root -p
```
For this book, you will need a computer with access to the Internet and the ability to install the open source software needed for the projects. The primary software we will be using consists of the R and Python programming languages, with a myriad of freely available packages and libraries. Installation instructions are in the first chapter.
## Related Products
* [Practical Data Science Cookbook](https://www.packtpub.com/big-data-and-business-intelligence/practical-data-science-cookbook?utm_source=github&utm_medium=repository&utm_campaign=9781783980246)
* [Python Data Science Essentials - Second Edition](https://www.packtpub.com/big-data-and-business-intelligence/python-data-science-essentials-second-edition?utm_source=github&utm_medium=repository&utm_campaign=9781786462138)
* [Practical Data Analysis - Second Edition](https://www.packtpub.com/big-data-and-business-intelligence/practical-data-analysis-second-edition?utm_source=github&utm_medium=repository&utm_campaign=9781785289712)
### Download a free PDF
If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.