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Mastering Machine Learning with R. Advanced prediction, algorithms, and learning methods with R 3.x - Second Edition

Mastering Machine Learning with R. Advanced prediction, algorithms, and learning methods with R 3.x - Second Edition

Cory Lesmeister

E-book
This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more.
You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you’ll understand how these concepts work and what they do.
With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.
  • 1. A Process for Success
  • 2. Linear Regression - the Blocking and Tackling of Machine Learning
  • 3. Logistic Regression and Discriminant Analysis
  • 4. Advanced Feature Selection in Linear Models
  • 5. More Classification Techniques - K-Nearest Neighbors and Support Vector Machines
  • 6. Classification and Regression Trees
  • 7. Neural Networks and Deep Learning
  • 8. Cluster Analysis
  • 9. Principal Components Analysis
  • 10. Market Basket Analysis, Recommendation Engines, and Sequential Analysis
  • 11. Creating Ensembles and Multi-Class Classification
  • 12. Time Series and Causality
  • 13. Text Mining
  • 14. R on the Cloud
  • 15. Appendix A: R Fundamentals
  • 16. Appendix B: Sources
  • Titel: Mastering Machine Learning with R. Advanced prediction, algorithms, and learning methods with R 3.x - Second Edition
  • Autor: Cory Lesmeister
  • Originaler Titel: Mastering Machine Learning with R. Advanced prediction, algorithms, and learning methods with R 3.x - Second Edition
  • ISBN: 9781787284487, 9781787284487
  • Veröffentlichungsdatum: 2017-04-24
  • Format: E-book
  • Artikelkennung: e_15i6
  • Verleger: Packt Publishing