How to Think about Data Science

Regular price €127.99
Regular price €133.99 Sale Sale price €127.99
A01=Diego Miranda-Saavedra
Adversarial Examples
Age Group_Uncategorized
Age Group_Uncategorized
Algorithmic Bias
Analytical
Association Rule
Association Rule Analysis
Association Rule Mining
Author_Diego Miranda-Saavedra
automatic-update
Autonomous Vehicles
Catastrophic Forgetting
Category1=Non-Fiction
Category=PBT
Category=UFM
Category=UN
Category=UYQ
Collaborative Filtering
Computational
COP=United Kingdom
Data
Data Breaches
Data Science
Delivery_Pre-order
eq_computing
eq_isMigrated=2
eq_non-fiction
GPA Score
Language_English
Machine Learning
Overfitted Model
PA=Temporarily unavailable
Precision Recall Curve
Predictive Analytics
Price_€100 and above
PS=Active
Quantitative
Recommender System
RFs
Roc Curve
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
Delivery/Collection within 10-20 working days

Our Delivery Time Frames Explained
2-4 Working Days: Available in-stock

10-20 Working Days
: On Backorder

Will Deliver When Available
: On Pre-Order or Reprinting

We ship your order once all items have arrived at our warehouse and are processed. Need those 2-4 day shipping items sooner? Just place a separate order for them!

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.

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.