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How to Think about Data Science

Diego Miranda-Saavedra
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Adversarial Examples
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Algorithmic Bias
Analytical
analytical thinking
artificial intelligence limits
Association Rule
Association Rule Analysis
Association Rule Mining
Author_Diego Miranda-Saavedra
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Autonomous Vehicles
Catastrophic Forgetting
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Collaborative Filtering
Computational
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Data
Data Breaches
Data Science
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ethical algorithms
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Language_English
Machine Learning
Overfitted Model
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practical data science applications
Precision Recall Curve
Predictive Analytics
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Quantitative
Recommender System
research methodology
RFs
Roc Curve
scientific inquiry
Semi-supervised Learning
Shewhart X-bar Charts
Simpson's Paradox
softlaunch
Supervised Machine Learning
SVMs
Trolley Problem
Tv Advertising
Underfitted Model
Visualisations

Product details

  • ISBN 9781032375687
  • Weight: 540g
  • Dimensions: 178 x 254mm
  • Publication Date: 23 Dec 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
  • Language: English
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Description
This book is a timely and critical introduction for those interested in what data science is (and isn’t), and how it should be applied. The language is conversational and the content is accessible for readers without a quantitative or computational background; but, at the same time, it is also a practical overview of the field for the more technical readers. The overarching goal is to demystify the field and teach the reader how to develop an analytical mindset instead of following recipes. The book takes the scientist’s approach of focusing on asking the right question at every step as this is the single most important factor contributing to the success of a data science project. Upon finishing this book, the reader should be asking more questions than I have answered. This book is, therefore, a practising scientist’s approach to explaining data science through questions and examples.
About Diego Miranda-Saavedra

Diego Miranda Saavedra is a data scientist and a financial investor with a technical management and business background. His formal education includes a PhD (data analysis), an MSc in business analytics, and an MS in software engineering from the University of Oxford.

As part of a research career in data science, Diego has made seminal contributions and worked in renowned research institutes around the world. These include the Wellcome Trust Biocentre (Dundee, UK), the Cambridge Institute for Medical Research (Cambridge, UK) and the WPI Immunology Frontier Research Center (Osaka University, Japan) where he led the bioinformatics and genomics research laboratory. While at the University of Cambridge, Diego was also elected a fellow of Wolfson College.

Diego also loves teaching data science and is currently an adjunct professor at the Faculty of Economics of the University of Groningen and at the Universitat Oberta de Catalunya.

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