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In my own blog I wrote a series of articles about how major machine learning classifiers work, with some visualization of their decision boundaries on various datasets.

- Machine learning for package users with R (0): Prologue
- Machine learning for package users with R (1): Decision Tree
- Machine learning for package users with R (2): Logistic Regression
- Machine learning for package users with R (3): Support Vector Machine
- Machine learning for package users with R (4): Neural Network
- Machine learning for package users with R (5): Random Forest
- Machine learning for package users with R (6): Xgboost (eXtreme Gra...
- What kind of decision boundaries does Deep Learning (Deep Belief Ne...

This series of the articles has a simple goal; to help many people understand an algorithm and theoretical features of each ML classifier easily. I believe visualization is the most important in particular.

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