Search query: practical data science with r

Product: Digitization and Digital Archiving (Practical Guides for Librarians, 71) (Volume 71)
Brand: Rowman & Littlefield Publishers
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Practical Data Science with R
Description: Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.

Business analysts and developers are increasingly collecting, curating, analyzing, and reporting on crucial business data. The R language and its associated tools provide a straightforward way to tackle day-to-day data science tasks without a lot of academic theory or advanced mathematics.

What's inside

Data science for the business professional

Statistical analysis using the R language

Project lifecycle, from planning to delivery

Numerous instantly familiar use cases

Keys to effective data presentations

This book is accessible to listeners without a background in data science. Some familiarity with basic statistics, R, or another scripting language is assumed.

Nina Zumel and John Mount are cofounders of a San Francisco-based data science consulting firm. Both hold PhDs from Carnegie Mellon and blog on statistics, probability, and computer science.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Practical Data Science With R [2nd Edition] (2020): Nina Zumel, John Mount, Jeremy Howard, Rachel Thomas (2020)
Description: Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science. You’ll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. Evidence-based decisions are crucial to success. Applying the right data analysis techniques to your carefully curated business data helps you make accurate predictions, identify trends, and spot trouble in advance. The R data analysis platform provides the tools you need to tackle day-to-day data analysis and machine learning tasks efficiently and effectively. Source Code available here: https://www.manning.com/downloads/2043
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Data Integrity and Data Governance: Practical Implementation in Regulated Laboratories
Description: Data integrity is the hottest topic in the pharmaceutical industry. Global regulatory agencies have issued guidance, after guidance after guidance in the past few years, most of which does not offer practical advice on how to implement policies, procedures and processes to ensure integrity. These guidances state what but not how. Additionally, key stages of analysis that impact data integrity are omitted entirely.
The aim of this book is to provide practical and detailed help on how to implement data integrity and data governance for regulated analytical laboratories working in or for the pharmaceutical industry. It provides clarification of the regulatory issues and trends, and gives practical methods for meeting regulatory requirements and guidance. Using a data integrity model as a basis, the principles of data integrity and data governance are expanded into practical steps for regulated laboratories to implement. The author uses case study examples to illustrate his points and provides instructions for applying the principles of data integrity and data governance to individual laboratory needs. This book is a useful reference for analytical chemists and scientists, management and senior management working in regulated laboratories requiring either an understanding about data integrity or help in implementing practical solutions. Consultants will also benefit from the practical guidance provided.
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Practical Data Science with R
Description: Printed in Asia - Carries Same Contents as of US edition - Opt Expedited Shipping for 3 to 4 day delivery -
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: A Primer on Process Mining: Practical Skills with Python and Graphviz (SpringerBriefs in Information Systems)
Brand: Springer
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Practical Data Science with R
Brand: Manning Publications
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data (Chapman & Hall/CRC Texts in Statistical Science)
Brand: Chapman and Hall/CRC
Chapman Hall
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Data Mining for Business Analytics: Concepts, Techniques, and Applications in R
Brand: Wiley
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): S

Product: Practical Time Series Analysis: Prediction with Statistics and Machine Learning
Brand: O'Reilly Media
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Practical Statistics for Data Scientists: 50 Essential Concepts
Brand: O'Reilly Media
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Brand: O'Reilly Media
O Reilly Media
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
Brand: Springer
This book presents some of the most important modeling and prediction techniques, along with relevant applications
Topics include linear regression, classification, re-sampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented.
Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Data Science Using Python and R (Wiley Series on Methods and Applications in Data Mining)
Brand: Wiley
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: R for Political Data Science (Chapman & Hall/CRC The R Series)
Brand: Chapman and Hall/CRC
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E

Product: Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Brand: O'Reilly Media
Relevance (ESCI, E=Exact S=Substitute C=Complement I=Irrelevant): E