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https://github.com/melling/handsonmachinelearningr


https://github.com/melling/handsonmachinelearningr

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README

          

# Hands-On Machine Learning R

Working through this book

https://bradleyboehmke.github.io/HOML/

- [Chapter 01 Notes: Introduction](chap01/README.md)
- [Chapter 02 Notes: Model Process](chap02/README.md) | [R Code](chap2/chapt02.Rmd)
- [Chapter 03 Notes: Feature & Target Engineering](chap03/README.md)
- [Chapter 04 Notes: Linear Regression](chap04/README.md)
- [Chapter 05 Notes: Logistic Regression](chap05/README.md)
- [Chapter 06 Notes: Regularized Regression](chap06/README.md)
- [Chapter 07 Notes: Multivariate Adaptive Regression Splines](chap07/README.md)
- [Chapter 08 Notes: K-Nearest Neighbors](chap08/README.md)
- [Chapter 09 Notes: Decision Trees](chap09/README.md)
- [Chapter 10 Notes: Bagging](chap10/README.md)
- [Chapter 11 Notes: Random Forests](chap11/README.md)
- [Chapter 12 Notes: Gradient Boosting](chap12/README.md)
- [Chapter 13 Notes: Deep Learning](chap13/README.md)
- [Chapter 14 Notes: Support Vector Machines](chap14/README.md)
- [Chapter 15 Notes: Stacked Models](chap15/README.md)
- [Chapter 16 Notes: Interpretable Machine Learning](chap16/README.md)
- [Chapter 17 Notes: Principal Components Analysis](chap17/README.md)
- [Chapter 18 Notes: Generalized Low Rank Models](chap18/README.md)
- [Chapter 19 Notes: Autoencoders](chap19/README.md)
- [Chapter 20 Notes: K-means Clustering](chap20/README.md)
- [Chapter 21 Notes: Hierarchical Clustering](chap21/README.md)
- [Chapter 22 Notes: Model-based Clustering](chap22/README.md)