Practical Data Science Cookbook
As an increasing amount of data is generated each year, and 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. This drives a higher demand for knowledgeable and competent data professionals. By sequentially working through the steps presented in each chapter, you will quickly familiarize yourself with the data science 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.
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Difficulty Level
Intermediate
Completion Time
14h28m
Language
English
About Book
Who Is This Book For?
If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python.
Practical Data Science Cookbook
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 14h28m total length
Preparing Your Data Science Environment
Driving Visual Analysis with Automobile Data with R
Creating Application-oriented Analyses Using Tax Data with Python
Modeling Stock Market Data
Visually Exploring Employment Data
Driving Visual Analyses with Automobile Data
Working with Social Graphs
Recommending Movies at Scale
Harvesting and Geolocating Twitter Data
Forecasting New Zealand Overseas Visitors
German Credit Data Analysis
Related Resources
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