Models Demystified: A Practical Guide from Linear Regression to Deep Learning
Author:   Michael Clark (Strong Analytics, U.S.A) ,  Seth Berry (University of Notre Dame, U.S.A)
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032582580


Pages:   474
Publication Date:   14 August 2025
Format:   Hardback
Availability:   Not yet available   Availability explained
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Models Demystified: A Practical Guide from Linear Regression to Deep Learning


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Full Product Details

Author:   Michael Clark (Strong Analytics, U.S.A) ,  Seth Berry (University of Notre Dame, U.S.A)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   1.070kg
ISBN:  

9781032582580


ISBN 10:   1032582588
Pages:   474
Publication Date:   14 August 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

1.Introduction 2.Thinking About Models 3.The Foundation 4.Understanding the Model 5.Understanding the Features 6.Model Estimation and Optimization 7.Estimating Uncertainty 8.Generalized Linear Models 9.Extending the Linear Model 10.Core Concepts in Machine Learning 11.Comon Models in Machine Learning 12.Extending Machine Learning 13.Causal Modeling 14.Dealing with Data 15.Danger Zone 16.Parting Thoughts

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Author Information

Michael Clark is a senior machine learning scientist for OneSix, and in prior stints, was a data science consultant at the University of Michigan and Notre Dame. His models have been used in production across a variety of industries, and can be seen in dozens of publications across several academic disciplines. He has a passion for helping people of all skill levels learn difficult stuff. Seth Berry is the Academic Co-Director of the Master of Science in Business Analytics (MSBA) Residential Program, and Associate Teaching Professor at the University of Notre Dame for the IT, Analytics, and Operations Department. He has a PhD in Applied Experimental Psychology, and has been teaching and consulting in data science for over a decade.

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