Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data.

Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings.

This new 3rd edition updates the classic R data science book to R 3.6 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R.

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Spis treści

Machine Learning with R. Expert techniques for predictive modeling - Third Edition eBook -- spis treści

• 1. Introducing Machine Learning
• 2. Managing and Understanding Data
• 3. Lazy Learning – Classification Using Nearest Neighbors
• 4. Probabilistic Learning – Classification Using Naive Bayes
• 5. Divide and Conquer – Classification Using Decision Trees and Rules
• 6. Forecasting Numeric Data – Regression Methods
• 7. Black Box Methods – Neural Networks and Support Vector Machines
• 8. Finding Patterns – Market Basket Analysis Using Association Rules
• 9. Finding Groups of Data – Clustering with k-means
• 10. Evaluating Model Performance
• 11. Improving Model Performance
• 12. Specialized Machine Learning Topics