General Introduction to Data Analytics

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A01=Andre Carvalho
A01=Joao Moreira
A01=Tomas Horvath
advanced predictive methods
agglomerative hierarchical clustering
algorithm bias
amazon data set
apriori
association rules
attribute values
Author_Andre Carvalho
Author_Joao Moreira
Author_Tomas Horvath
binary classification task
Category=GPH
classification algorithms
client segmentation
clustering
clustering techniques
clustering validation
crisp-dm
data
data analytics
data extraction
data scientists
data set
dbscan technique
descriptive analytics
descriptive statistics
distance measures
eclat
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
frequent itemsets
frequent pattern mining
information retrieval
k-means
kdd
machine learning
marketbasket data set
medicine data set
multiclass classification tasks
partition evaluation measures
predictive analytics
pseudo code
recommender systems
social network analysis
statistics
visualizing data

Product details

  • ISBN 9781119296249
  • Weight: 726g
  • Dimensions: 155 x 226mm
  • Publication Date: 24 Aug 2018
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
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A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming

A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples.

Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer:

  • A guide to the reasoning behind data mining techniques
  • A unique illustrative example that extends throughout all the chapters
  • Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts

Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic.

The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.

João Mendes Moreira, PhD, is an assistant professor in the Faculty of Engineering at the University of Porto, Porto, Portugal and is also a researcher in LIAAD-INESC TEC, Porto, Portugal.

André de Carvalho, PhD, is a full professor in the Institute of Mathematics and Computer Science at the University of São Paulo, Brazil.

Tomáš Horváth, PhD, is an assistant professor at the Faculty of Informatics of the Eötvös Loránd University in Budapest, Hungary, and is also associated with the Faculty of Science at the Pavol Jozef Šafárik University in Košice, Slovakia.

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