Lecture notes

OpenStax

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Machine learning lecture 1 course notes

1 Supervised learning

2 Linear regression

3 Lms algorithm

4 The normal equations

5 Matrix derivatives

6 Least squares revisited

7 Probabilistic interpretation

8 Locally weighted linear regression

9 Classification and logistic regression

10 Logistic regression

11 Digression: the perceptron learning algorithm

12 Another algorithm for maximizing ℓ ( θ )

13 Generalized linear models The presentation of the material in this

14 The exponential family

15 Constructing glms

16 Ordinary least squares

17 Logistic regression

18 Softmax regression

Machine learning lecture 2 course notes

Machine learning lecture 3 course notes

Machine learning lecture 4 course notes

Machine learning lecture 5 course notes

Machine learning lecture 6 course notes

Machine learning lecture 7a course notes

Machine learning lecture 7b course notes

Machine learning lecture 8 course notes

Machine learning lecture 9 course notes

Machine learning lecture 10 course notes

Machine learning lecture 11 course notes

Machine learning lecture 12 course notes

Source: OpenStax, Machine learning. OpenStax CNX. Oct 14, 2013 Download for free at http://cnx.org/content/col11500/1.4

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