Code for Machine Learning for Hackers

February 16, 2012 | Drew Conway

With the release of the eBook version of Machine Learning for Hackers this week, many people have been asking for the code. With good reason—as it turns out—because O’Reilly still (at the time of this writing) has not updated the book page to include a link to ... [Read more...]

Machine Learning Ex2 – Linear Regression

March 22, 2011 | R on Guangchuang Yu

Thanks to this post, I found OpenClassroom. In addition, thanks to Andrew Ng and his lectures, I took my first course in machine learning. These videos are quite easy to follow. Exercise 2 requires implementing gradient descent algorithm to model data with linear regression. Read More: 243 Words Totally
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Machine Learning Ex5.2 – Regularized Logistic Regression

March 20, 2011 | al3xandr3

Exercise 5.2 Improves the Logistic Regression implementation done in Exercise 4 by adding a regularization parameter that reduces the problem of over-fitting. We will be using Newton's Method. Data Here's the data we want to fit. # linear regression # load the data mydata = read.csv("
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Machine Learning Ex5.1 – Regularized Linear Regression

March 18, 2011 | al3xandr3

Exercise 5.1 Improves the Linear Regression implementation done in Exercise 3 by adding a regularization parameter that reduces the problem of over-fitting. Over-fitting occurs especially when fitting a high-order polynomial, that we will try to do here. Data Here's the points we will make a model from: # linear regression mydata = read.csv("...
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Language used by Academics with the Protection of Anonymity

March 14, 2011 | Drew Conway

Those in the political science discipline probably remember their first encounter with For those outside, you have probably never heard of this particular message board, and you would have no reason to. As the URL suggests, the board specializes in rumor, gossip, back-bitting, mudslinging, and the occasional lucid ... [Read more...]

Machine Learning Ex3 – multivariate linear regression

March 8, 2011 | al3xandr3

Exercise 3 is about multivariate linear regression. First part is about finding a good learning rate (alpha) and 2nd part is about implementing linear regression using normal equations instead of the gradient descent algorithm. Data As usual hosted in google docs: mydata = read.csv("
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Machine Learning Ex2 – linear regression

February 24, 2011 | al3xandr3

Andrew Ng has posted introductory machine learning lessons on the OpenClassRoom site. I've watched the first set and will here solve Exercise 2. The exercise is to build a linear regression implementation, I'll use R. The point of linear regression is to come up with a mathematical function(model) that represents ...
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