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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...

Linear Algebra and Probability for Computer Science Applications
Linear Algebra and Probability for Computer Science Applications

Based on the author’s course at NYU, Linear Algebra and Probability for Computer Science Applications gives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the...

Understanding Statistics Using R
Understanding Statistics Using R

This book was written to provide resource materials for teachers to use in their introductory or intermediate statistics class. The  chapter content is ordered along the lines of many popular statistics books so it should be easy to supplement the content and exercises with class lecture materials. 

The book...

Computational Statistics: An Introduction to R
Computational Statistics: An Introduction to R

Suitable for a compact course or self-study, Computational Statistics: An Introduction to R illustrates how to use the freely available R software package for data analysis, statistical programming, and graphics. Integrating R code and examples throughout, the text only requires basic knowledge of statistics and...

Service-Oriented Crowdsourcing: Architecture, Protocols and Algorithms (SpringerBriefs in Computer Science)
Service-Oriented Crowdsourcing: Architecture, Protocols and Algorithms (SpringerBriefs in Computer Science)
At a fundamental level, service-oriented crowdsourcing applies the principles of service-oriented architecture (SOA) to the discovery, composition and selection of a scalable human workforce. Service-Oriented Crowdsourcing: Architecture, Protocols and Algorithms provides both an analysis of contemporary crowdsourcing systems, such as Amazon...
Natural Language Processing and Computational Linguistics: A practical guide to text analysis with Python, Gensim, spaCy, and Keras
Natural Language Processing and Computational Linguistics: A practical guide to text analysis with Python, Gensim, spaCy, and Keras

Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms.

Key Features

  • Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and...
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition

The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and...

Robustness and Complex Data Structures
Robustness and Complex Data Structures
Our journey towards this Festschrift started when realizing that our teacher, mentor, and friend Ursula Gather was going to celebrate her 60th birthday soon. As a researcher, lecturer, scientific advisor, board member, reviewer, editor, Ursula has had a wide impact...
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute...

The R Book
The R Book

Hugely successful and popular text presenting an extensive and comprehensive guide for all R users

The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help...

ggplot2: Elegant Graphics for Data Analysis (Use R!)
ggplot2: Elegant Graphics for Data Analysis (Use R!)
ggplot2 is an R package for producing statistical, or data, graphics, but it is unlike most other graphics packages because it has a deep underlying grammar. This grammar, based on the Grammar of Graphics (Wilkinson, 2005), is composed of a set of independent components that can be composed in many different...
Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable...
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