A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R
The only how-to guide offering a unified, systemic approach to acquiring, cleaning, and managing data in R
Every experienced practitioner knows that preparing data for modeling is a painstaking, time-consuming process. Adding to the difficulty is that most modelers learn the steps involved in cleaning and managing data...
Developing Analytic Talent: Becoming a Data Scientist
Learn what it takes to succeed in the the most in-demand tech job
Harvard Business Review calls it the sexiest tech job of the 21st century. Data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented IT...
The Data Science Design Manual (Texts in Computer Science)
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data.
Data Science from Scratch: First Principles with Python
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from...
Practical Data Science Cookbook - Second Edition
Over 85 recipes to help you complete real-world data science projects in R and Python
About This Book
Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data
Get beyond the theory and implement real-world projects in data science using...
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