Machine Learning Podcast Learning Notes Apr 18

1. Support Vector Machine (SVM): draw a fat line, like a wall, to classify data set into different categories, dots are support vector and it is used to solve over-fitting problem (vs logistic regression).


Non-linear data set can be “converted” to linear ones with Kernel, which is like a goggle, look at the world in a different angle (dark to light).

2. Naive Bayes Classifier

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Pattern Recognition and Machine Learning

Machine Learning with R

Machine Learning Map

Machine Learning Algorithms Pros and Cons

Mathematical Decision Making: Predictive Models and Optimization


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