Hands-on tested · Updated 2026
Completely free - no payment needed.
Where it falls short
May be challenging for beginners
Written by Max Kuhn and Kjell Johnson, 'Applied Predictive Modeling' is a classic educational book that delves into data modeling methods. The book covers a range of modeling techniques from basic to advanced, suitable for data scientists and analysts. The content is comprehensive and suitable for self-study, although it may be challenging for beginners. In summary, it is a recommended toolbook.
From registration to actual use - step by step
Visit AppliedPredictiveModeling.com to access Kuhn & Johnson's Applied Predictive Modeling.
View BookAuthors created the caret package; the authoritative R predictive modeling practice guide.
Systematically learn data preprocessing, feature selection, model training, tuning, and evaluation.
Companion caret package code unifies algorithm interfaces, simplifying modeling workflow.
Learn linear regression, decision trees, random forests, SVM applications and comparisons.
Focus on model tuning chapters; key to improving model performance.
Apply methods to solve book case problems like churn prediction and quality forecasting.
For R data scientists; essential reference for caret package usage.
💡 Applied Predictive Modeling by Max Kuhn and Kjell Johnson is a software tool, not an AI model. To experience its full features, please visit the official website. You can also add it to your workflow below.
Suitable for data scientists, analysts, and data modeling enthusiasts. ## How to Use 1. Visit the website 2. Download the e-book or purchase the physical book 3. Read and learn
Applied Predictive Modeling by Max Kuhn and Kjell Johnson is a free tool. Visit the official website for detailed pricing.
View pricing →| Tool | Rating | Pricing | Best For |
|---|---|---|---|
| Applied Predictive Modeling by Max Kuhn and Kjell Johnson ★ | 0/5 | Free | Education |
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