Practical Data Science

Abstract

Data's value has grown exponentially in the past decade, with 'Big Data' today being one of the biggest buzzwords in business and IT, and data scientist hailed as 'the sexiest job of the 21st century'. Practical Data Science Cookbook helps you see beyond the hype and get past the theory by providing you with a hands-on exploration of data science. With a comprehensive range of recipes designed to help you learn fundamental data science tasks, you'll uncover practical steps to help you produce powerful insights into Big Data using R and Python. Use this valuable data science book to discover tricks and techniques to get to grips with your data. Learn effective data visualization with an automobile fuel efficiency data project, analyze football statistics, learn how to create data simulations, and get to grips with stock market data to learn data modelling. Find out how to produce sharp insights into social media data by following data science tutorials that demonstrate the best ways to tackle Twitter data, and uncover recipes that will help you dive in and explore Big Data through movie recommendation databases. With further guidance on optimizing numerical code using NumPy and SciPy, this cookbook provides you with all the tools to become a successful and intelligent data scientist. Practical Data Science Cookbook is your essential companion to the real-world challenges of working with data, created to give you a deeper insight into a world of Big Data that promises to keep growing. Follow the recipes in this essential data science cookbook to learn the fundamentals of data science and data analysis Put theory into practice with a selection of real-world Big Data projects Learn the data science pipeline and successfully structure your data science project Learn how to harness the impressive capabilities of R and Python for data science Find out how to clean, munge, and manipulate data to prepare it for analysis Learn different approaches to data modelling and how to determine the most appropriate for your data Dive into numerical programming with recipes on optimizing code with NumPy and SciPy