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Probability: With Applications and R
Probability: With Applications and R

An introduction to probability at the undergraduate level

Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability.

...
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...

Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Now updated—the systematic introductory guide to modern analysis of large data sets

As data sets continue to grow in size and complexity, there has been an inevitable move towards indirect, automatic, and intelligent data analysis in which the analyst works via more complex and sophisticated software tools. This book...

Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

Practical Data Wrangling: Expert techniques for transforming your raw data into a valuable source for analytics
Practical Data Wrangling: Expert techniques for transforming your raw data into a valuable source for analytics

Key Features

  • This easy-to-follow guide takes you through every step of the data wrangling process in the best possible way
  • Work with different types of datasets, and reshape the layout of your data to make it easier for analysis
  • Get simple examples and real-life data...
Multivariate Time Series Analysis: With R and Financial Applications
Multivariate Time Series Analysis: With R and Financial Applications

An accessible guide to the multivariate time series tools used in numerous real-world applications

Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a...

Introductory Statistics with R (Statistics and Computing)
Introductory Statistics with R (Statistics and Computing)
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the...
Data Mining and Statistics for Decision Making
Data Mining and Statistics for Decision Making
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify...
Elasticsearch: A Complete Guide
Elasticsearch: A Complete Guide

End-to-end Search and Analytics

About This Book

  • Solve your data analytics problems with the Elastic Stack
  • Improve your user search experience with Elasticsearch and develop your own Elasticsearch plugins
  • Design your index, configure it, and distribute it ― you'll...
Inference Control in Statistical Databases: From Theory to Practice (Lecture Notes in Computer Science)
Inference Control in Statistical Databases: From Theory to Practice (Lecture Notes in Computer Science)
Inference control in statistical databases, also known as statistical disclosure limitation or statistical confidentiality, is about finding tradeoffs to the tension between the increasing societal need for accurate statistical data and the legal and ethical obligation to protect privacy of individuals and enterprises which are the source...
Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist
Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.

Beginning Data Science in R...
Sudoku Programming with C
Sudoku Programming with C

Sudoku Programming with C teaches you how to write computer programs to solve and generate Sudoku puzzles. This is a practical book that will provide you with everything you need to write your own books of Sudoku Classic and Samurai puzzles. But be warned: after reading it, you'll discover that the puzzles in...

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