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Google's keynote on doing machine learning using quantum computing....

submitted by aboo0ood [link] [4 comments]

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Representative ensemble learning methods?

I am now collecting some materials for a PPT about ensemble learning. However, I am not sure which ensemble learning methods should be put into the slides. Any suggestions? submitted by Yonah27 [link]...

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Optimization Algorithms in Machine Learning

submitted by cavedave [link] [comment]

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How can I get started in Predictive Analytics?

I have a BS in Finance from about 15 years ago but have mainly used it for basic accounting, modeling and financial reporting roles. I am interested in learning how to build predictive models related...

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Model Selection vs. Parameter Estimation vs. Optimization

In the context of machine learning what is the difference between the terms models selection, parameter estimation and optimization. I don't think the terms are interchangeable, especially in machine...

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Computing solutions for crunching large datasets?

Hey all, I'm starting to work on an indpendent project or two with some engineering and economist friends of mine, and we're realizing that we don't really have the computing power at our disposal to...

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AskML: How much confidence can one have in nested cross-validation results?

I posted this on the Kernel Machines forum, but I thought I would try my luck here, too: In short, I am wondering how much confidence to have in the results of nested cross-validation after noticing...

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Operations Research, Machine Learning, and Optimization

submitted by cavedave [link] [6 comments]

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High False Negative Rate in Binary Text Classification

I am looking for some advice on how to accomplish a lower false negative rate in a binary classifier. I was taught to always start with Naive Bayes (if it has any hope of being decent) and then move on...

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Machine Learning with Python

(xpost from /r/learnprogramming because I hadn't known this subreddit existed) Hi, so I'm trying to learn how to use Orange with python to do data comparisons, and machine learning to make educated...

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What are some metrics I can use to measure the similarity/distance between a...

EDIT: Just to clarify, the basic solution I can come up with is to do a comparison between each time series of the two different items and a comparison between the spatial values of the same items and...

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What do you guys think of Northwestn's Master of Science in Predictive...

I am currently enrolled in Data Mining Certificate - UC San Diego Extension and want to get more out of this subject than a certificate. I came across Northwestern's Master of Science in Predictive...

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X-post from r/statistics: How to rank products based on user input

submitted by jackhammer2022 [link] [comment]

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More Precious than Gold?

submitted by cavedave [link] [comment]

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Homework advice - Clustering w/o K-Means?

Hello all, I'm working on a data mining project that ends with me clustering bag-of-words type data. The majority of the project so far has been pre-processing (the data is an awesome web-crawled data...

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Ask ML: While training sparse autoencoders, how do you decide values for the...

submitted by strayadvice [link] [33 comments]

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All TIME Magazine covers (March 1923 to March 2012). X-post from r/datasets

I found this in /r/datasets posted by "trexmatt" Post Link Download Link. I am a datamining noob, and I have an idea for a data mining exercise with these covers. I would like to get some guidance on...

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Extracting Structure on a Very Complexly Interacting Feature Space

Consider the case where you have a dataset with fairly low dimensionality and a very high number of data points. One such that in most supervised learning approaches you'd be more concerned with...

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Can someone explain the Perceptron Learning Algorithm to me? Like I'm a...

I'm trying to slog through the Caltech online course called "Learning from Data." We haven't even turned in the first homework yet, and I'm lost. We're supposed to code our own PLA: Create 100 random...

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Linear Regression with nonlinear parameters

Trying to solve a rather simple multiple linear regression problem on a function, whose form resembles the logarithmic curve, I added log(x+1) for each parameter x to the parameter vector. I determine...

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