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Machine Learning Books

I have been collecting machine learning books over the past couple months. It seems that machine learning professors are good about posting free legal pdfs of their work. I hope they are useful to you....

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Texture descriptors based on oriented gradients?

I asked a previous question yesterday. The post can be found here. The post has many details that I'm going to reference below. I have a k-means segmented image that represents a terrestrial site. The...

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How easy/difficult is it for a programmer with machine learning experience or...

I've been thinking about this a lot lately. I was a statistics major as an undergrad with a minor in computer science. I'm in graduate school now getting a master's degree in Software Engineering. I...

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Constrained Independent Component Analysis (cICA)

Does anyone have any experience with constrained independent component analysis? Have been trying to implement cICA in matlab for a while now and cannot get it to work. Following exactly the algorithm...

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Eric Schmidt says that a computer will Pass the Turing Test in 5 Years

submitted by wisintel [link][10 comments]

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Simple question about Gibbs Sampling with a single Dirichlet-Multinomial

I assume the most simple model:theta | alpha ~ Dir(alpha + N)X_i | Discrete(theta), i = 1, 2, 3What would be the update equation, p(x_i, x_-i)? Is it the predictive distribution of a...

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Bayesian Analysis of Normal Distributions with Python

submitted by sergeyfeldman [link][comment]

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What does Linear Algebra have to do with Machine Learning?

I'm currently taking an advanced Linear Algebra course on Linear Dynamic Systems, and we're covering things like Least-Squares Approximation, Multi-Objective Least Squares, finding the Least-Norm...

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Improve your Machine Learning with this one weird trick.

submitted by SCombinator [link][6 comments]

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Why don't sigmoid and tanh neural nets behave equivalently?

A sigmoid net can emulate a tanh net of the same architecture, and vice versa. I calculated the gradient for a tanh net, and used the chain rule to find the corresponding gradient for a sigmoid net...

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How can an ensemble of predictive models provide better predictions than any...

Consider a situation where we have 99 mediocre predictive models, and 1 good one. The models are tasked with predicting the probability of a particular classification. We combine the model's...

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Who is attending the European Conference on Machine Learning in Prague?

I am curious. I am coming from Canada to present a paper at the Sports Analytics workshop. submitted by ScullerLite [link][11 comments]

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Can someone explain Kernel Trick intuitively?

submitted by Intern_MSFT [link][comment]

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With Hinton's DREDNETs, what happened to semi-supervised density modeling?

I've been trying to wrap my head around the Deep Learning scene for a while now, but I'm merely an enthusiast and get a little lost in the details once in a while. Following the literature over the...

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Calculate significant differences of classifier results for a corpus

In the paper http://nlp.stanford.edu/pubs/sidaw12_simple_sentiment.pdf they calculated "The approximate upper-bounds on the difference required to be statistically significant at the p < 0.05 level...

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Suggestions for visualizing high-dimensional clusters

For example, how would you visualize the results of doing k-means on the 20 newsgroups? Looking for a few ideas for projecting sparse document vectors down to 2- or 3-D, just so I can draw some pretty...

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Impressions from ICML 2013

submitted by urish [link][1 comment]

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climin; optimization, straight forward

submitted by sieisteinmodel [link][comment]

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Introduction to Recommender Systems

submitted by chocolategirl [link][1 comment]

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Theoretical Limits in Machine Learning for the NHL

submitted by ScullerLite [link][comment]

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