Practical Data Science Cookbook is published by Packt Publishing in June 2017. This book has 458 pages in English, ISBN-13 978-1787129627.
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.
What you will learn
- Get to know the installation procedure and environment required for R and Python on various platforms
- Implement data science concepts such as acquisition, munging, and analysis through R and Python
- Analyze and produce reports on data
- Perform some text mining
- Build a predictive model and an exploratory model
- Build various tree-based methods and Build random forest