Stanford CS229 Lecture Note

1.[Stanford CS229] Lecture1 - Machine Learning

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2.[Stanford CS229] Lecture2 - Linear Regression and Gradient Descent

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3.[Stanford CS229] Lecture3 - Locally Weighted & Logistic Regression

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4.[Stanford CS229] Lecture4 - Perceptron & Generalized Linear Model

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5.[Stanford CS229]Lecture 5 : GDA & Naive Bayes

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6.[Stanford CS229]Lecture 6 : Support Vector Machines

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7.[Stanford CS229] Lecture7 - Kernels

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8.[Stanford CS229] Lecture8 - Data Splits, Models & Cross-Validation

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