Practical Machine Learning with R: Tutorials and Case Studies
Author:   Carsten Lange (Professor of Economics, Cal Poly Pomona, USA.)
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032434056


Pages:   352
Publication Date:   20 May 2024
Format:   Hardback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Practical Machine Learning with R: Tutorials and Case Studies


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Author:   Carsten Lange (Professor of Economics, Cal Poly Pomona, USA.)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   1.060kg
ISBN:  

9781032434056


ISBN 10:   1032434058
Pages:   352
Publication Date:   20 May 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1. Introduction 2. Basics of Machine Learning 3. Introduction to R and RStudio 4. k-Nearest Neighbors — Getting Started 5. Linear Regression — Key Machine Learning Concepts 6. Polynomial Regression — Overfitting & Tuning Explained 7. Ridge, Lasso, and Elastic Net — Regularization Explained 8. Logistic Regression — Handling Imbalanced Data 9. Deep Learning — MLP Neural Networks Explained 10. Tree-Based Models — Bootstrapping Explained 11. Interpreting Machine Learning Results 12. Concluding Remarks Index Bibliography

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Author Information

Carsten Lange is an economics professor at Cal Poly Pomona with a keen interest in making data science and machine learning more accessible. He has authored multiple refereed articles and four books, including his 2004 book on applying neural networks for economics. Carsten is passionate about teaching machine learning and artificial intelligence with a focus on practical applications and hands-on learning.

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