Bibliograph

Data science for business, [what you need to know about data mining and data-analytic thinking], Foster Provost and Tom Fawcett

Type

Label

Data science for business, [what you need to know about data mining and data-analytic thinking], Foster Provost and Tom Fawcett

Language

eng

Bibliography note

Includes bibliographical references (p. 359-366) and index

Illustrations

illustrations

Index

index present

Literary Form

non fiction

Main title

Data science for business

Nature of contents

bibliography

Oclc number

844460899

Responsibility statement

Foster Provost and Tom Fawcett

Sub title

[what you need to know about data mining and data-analytic thinking]

Summary

Provides an introduction to the fundamental principles of data science, walking the reader through the "data-analytic thinking" necessary for extracting useful knowledge and business value from collected data

Table Of Contents

Introduction : data-analytic thinking -- Business problems and data science solutions -- Introduction to predictive modeling : from correlation to supervised segmentation -- Fitting a model to data -- Overfitting and its avoidance -- Similarity, neighbors, and clusters -- Decision analytic thinking I : what is a good model? -- Visualizing model performance -- Evidence and probabilities -- Representing and mining text -- Decision analytic thinking II : toward analytical engineering -- Other data science tasks and techniques -- Data science and business strategy -- Conclusion

resource.variantTitle

What you need to know about data mining and data-analytic thinking

Contributor