Michael Clark, Seth Berry

Models Demystified

A Practical Guide from Linear Regression to Deep Learning

• Gebundenes Buch

Produktbeschreibung

In this comprehensive guide, we delve into the world of data science, machine learning, and AI modeling, providing readers with a robust foundation and practical skills to tackle real-world problems.

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Produktdetails

• Verlag: Taylor & Francis Ltd
• Seitenzahl: 508
• Erscheinungstermin: 8. August 2025
• Englisch
• Abmessung: 234mm x 156mm
• Gewicht: 453g
• ISBN-13: 9781032582580
• ISBN-10: 1032582588
• Artikelnr.: 73332579

Autorenporträt

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.

Inhaltsangabe

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