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The 9 Pitfalls of Data Science. Gary Smith, Jay Cordes

The-9-Pitfalls-of-Data.pdf
ISBN: 9780198844396 | 272 pages | 7 Mb

• The 9 Pitfalls of Data Science
• Gary Smith, Jay Cordes
• Page: 272
• Format: pdf, ePub, fb2, mobi
• ISBN: 9780198844396
• Publisher: Oxford University Press

Download The 9 Pitfalls of Data Science

Electronics data book free download The 9 Pitfalls of Data Science 9780198844396 in English by Gary Smith, Jay Cordes

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. Gary Smith and Jay Cordes emphasise how scientific rigor and critical thinking skills are indispensable in this age of Big Data, as machines often find meaningless patterns that can lead to dangerous false conclusions. The 9 Pitfalls of Data Science is loaded with entertaining tales of both successful and misguided approaches to interpreting data, both grand successes and epic failures. These cautionary tales will not only help data scientists be more effective, but also help the public distinguish between good and bad data science.

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Data science is the key to business success in the information economy. We will also talk about the many pitfalls and how to avoid them. prior): 5% for 2–4 people, 10% for 5–6 people, 15% for 7–8 people, and 20% for 9 or more people. Avoiding common pitfalls when clustering biological data | Science
Avoiding common pitfalls when clustering biological data Article; Figures & Data; Info & Metrics; eLetters; PDF Science Signaling: 9 (432)  Common data science pitfalls (article) - DataCamp
In this tutorial, you'll learn about some pitfalls you might experience when working on data science projects "in the wild". The 9 Pitfalls of Data Science (English Edition) eBook - Amazon
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   Data Pitfalls —the Startup Edition - Monica Rogati - Medium
A version of this article originally appeared in the Lean Analytics book 9. The “ Not Collected Here” syndrome: Mashing up your data with data  Data Science and Big Data Analytics: Making Data-Driven Decisions
Solve Complex Issues With Your Data. Identify and avoid common pitfalls in big data analytics. Deploy machine learning algorithms to mine your data. Ditch the data scientists and weaponize your data with AI tech (VB
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