Screen LibraryThe 9 pitfalls of data science /
Data science has never had more influence on the world. Large companies are now seeing the benefit of employing data scientists to interpret the vast amounts of data that now exists. However, the field is so new and is evolving so rapidly that the analysis produced can be haphazard at best. 'Th...
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| Main Authors: | |
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| Published: |
Oxford University Press,
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| Publisher Address: | Oxford : |
| Publication Dates: | 2019. |
| Literature type: | Book |
| Language: | English |
| Edition: | First edition. |
| Subjects: | |
| Summary: |
Data science has never had more influence on the world. Large companies are now seeing the benefit of employing data scientists to interpret the vast amounts of data that now exists. However, the field is so new and is evolving so rapidly that the analysis produced can be haphazard at best. 'The 9 Pitfalls of Data Science' shows us real-world examples of what can go wrong. Written to be an entertaining read, this invaluable guide investigates the all too common mistakes of data scientists - who can be plagued by lazy thinking, whims, hunches, and prejudices - and indicates how they have been at the root of many disasters, including the Great Recession. |
| Carrier Form: | v, 256 pages : illustrations (some color), color map ; 21 cm |
| Bibliography: | Includes bibliographical references (pages 241-252) and index. |
| ISBN: |
9780198844396 0198844395 |
| Index Number: | QA76 |
| CLC: | TP311.13 |
| Call Number: | TP311.13/S648 |
| Contents: | Using bad data -- Putting data before theory -- Worshiping math -- Worshiping computers -- Torturing data -- Fooling yourself -- Confusing correlation with causation -- Being surprised by regression toward the mean -- Doing harm -- Case study : the Great Recession. |