Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R

Buy

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 piecemeal, often on the fly, or they develop their own ad hoc methods. This book helps simplify their task by providing a unified, systematic approach to acquiring, modeling, manipulating, cleaning, and maintaining data in R. 

Starting with the very basics, data scientists Samuel E. Buttrey and Lyn R. Whitaker walk readers through the entire process. From what data looks like and what it should look like, they progress through all the steps involved in getting data ready for modeling.  They describe best practices for acquiring data from numerous sources; explore key issues in data handling, including text/regular expressions, big data, parallel processing, merging, matching, and checking for duplicates; and outline highly efficient and reliable techniques for documenting data and recordkeeping, including audit trails, getting data back out of R, and more.

  • The only single-source guide to R data and its preparation, it describes best practices for acquiring, manipulating, cleaning, and maintaining data
  • Begins with the basics and walks readers through all the steps necessary to get data ready for the modeling process
  • Provides expert guidance on how to document the processes described so that they are reproducible
  • Written by seasoned professionals, it provides both introductory and advanced techniques
  • Features case studies with supporting data and R code, hosted on a companion website

A Data Scientist's Guide to Acquiring, Cleaning and Managing Data in R is a valuable working resource/bench manual for practitioners who collect and analyze data, lab scientists and research associates of all levels of experience, and graduate-level data mining students.

(HTML tags aren't allowed.)

Python Requests Essentials
Python Requests Essentials

Learn how to integrate your applications seamlessly with web services using Python Requests

About This Book

  • A fast-paced guide that demonstrates the use of Python Requests with the help of examples
  • Learn web scraping with Beautiful Soup and Python Requests libraries
  • ...
Hadoop Real World Solutions Cookbook - Second Edition
Hadoop Real World Solutions Cookbook - Second Edition

Key Features

  • Implement outstanding Machine Learning use cases on your own analytics models and processes.
  • Solutions to common problems when working with the Hadoop ecosystem.
  • Step-by-step implementation of end-to-end big data use cases.

Who This Book Is For

...

Sql: Learn Basics of Queries and Implement Easily (sql programming, SQL 2016, sql database programming, sql for beginners, sql beginners guide, sql ... sql workbook,sql guide,MSSQL) (Volume 1)
Sql: Learn Basics of Queries and Implement Easily (sql programming, SQL 2016, sql database programming, sql for beginners, sql beginners guide, sql ... sql workbook,sql guide,MSSQL) (Volume 1)

SQL is a standard language for getting to and controlling databases. What is SQL? SQL remains for Structured Query Language SQL gives you a chance to get to and control databases SQL is an ANSI (American National Standards Institute) standard What Can SQL do? SQL can execute queries against a database SQL can get data from a database SQL can...


Doing Math with Python: Use Programming to Explore Algebra, Statistics, Calculus, and More!
Doing Math with Python: Use Programming to Explore Algebra, Statistics, Calculus, and More!

Doing Math with Python shows you how to use Python to delve into high school–level math topics like statistics, geometry, probability, and calculus. You’ll start with simple projects, like a factoring program and a quadratic-equation solver, and then create more complex projects once you’ve gotten the hang of...

Deep Learning with Python: A Hands-on Introduction
Deep Learning with Python: A Hands-on Introduction
Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often...
Think Python: How to Think Like a Computer Scientist
Think Python: How to Think Like a Computer Scientist

If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have...

©2018 LearnIT (support@pdfchm.net) - Privacy Policy