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Questions tagged [machine-learning]

relates to algorithms that are "trained" by some data set.

Machine-learning relates to algorithms that improve themselves, either during runtime, or trained beforehand. Neural networks, eigenfaces and genetic algorithms are examples of techniques employed in machine-learning.

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Simple method for reliably detecting code in text?

GMail has this feature where it will warn you if you try to send an email that it thinks might have an attachment. Because GMail detected the string see the attached in the email, but no actual attachment, it warns me with an OK / Cancel dialog…
Jeff Atwood
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R vs Python for data analysis

I have been programming for about a year and I am really interested in data analysis and machine learning. I am taking part in a couple of online courses and am reading a couple of books. Everything I am doing uses either R or Python and I am…
The_Cthulhu_Kid
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Decision trees vs. Neural Networks

I'm implementing a machine learning structure to try and predict fraud on financial systems like banks, etc... This means that there is a lot of different data that can be used to train the model eg. card number, card holder name, amount, country,…
Topo
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Machine learning applied to code development

My background is in mechanical engineering, so please forgive my ignorance to this area. I really enjoy programming and software development. Also, I recently took a free online Machine Learning (ML) class, which I highly recommend, taught by…
Charles
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How is machine learning incorporated into search engine design?

I am currently building a small in-house search engine based on Apache Lucene. Its purpose is simple - based on some keywords, it will suggest some articles written internally within our company. I am using a fairly standard TF-IDF scoring as a base…
Legend
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What does it mean for an algorithm to converge?

I keep coming across this term when reading about reinforcement learning, for example in this sentence: If the problem is modelled with care, some Reinforcement Learning algorithms can converge to the global optimum (source) or here: For any…
starfish
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Switching to a career in Machine Learning

My day job is plain old software development. I am also doing my Masters in CS (part time, course based). I took a course on AI and found machine learning quite fascinating but like most courses it only offered a basic intro. I intend to learn more…
Naive Machine Learner
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Is it imaginable to teach a machine how to program itself to a defined specification?

A friend of mine without programming knowledge asked me this question and I found it interesting. I think it is not possible because it would require a really advanced artificial intelligence capable of analyzing the text of a problem, think about a…
grandouassou
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Learning the rules of chess

A similar question asks whether a computer can learn to play optimally in chess by analyzing thousands of games. If a machine can look at the state of the board for a few games of chess (or a few games of checkers) in the beginning and after each…
Yktula
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Can a neural network provide more than "yes" or "no" answers?

Every example neural network for image recognition I've read about produces a simple "yes" or "no" answer. One exit node corresponds to "Yes, this is a human face," and one corresponds to "No, this is not a human face." I understand that this is…
asteri
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What math skills are required to learn machine learning?

I am interested in taking this online course on machine learning. As it stands my math is very elementary, and I am basically learning math from scratch on khan academy. Programming-wise I have a decent amount of experience, and a good overall…
levi
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What algorithm(s) can be used to achieve reasonably good next word prediction?

What is a good way of implementing "next-word prediction"? For example, the user types "I am" and the system suggests "a" and "not" (or possibly others) as the next word. I am aware of a method that uses Markov Chains and some training…
yati sagade
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Machine Learning With Categorical and Continuous Data

This question could go here or on S.O. perhaps... Suppose that your training dataset contains both categorical and continuous data such as this setup: Animal, breed, sex, age, weight, blood_pressure, annual_cost cat, calico, M, 10, 15 ,…
reptilicus
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Using machine learning to aim mirrors in a solar array?

I've been thinking about solar collectors where several independent mirrors to focus the light on a solar collector, similar to the following design from Energy Innovations. Because there will be flaws in the assembly of this solar array, I am…
Buttons840
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What's the best way to learn image processing?

I'm a senior in college that hasn't done much image processing before (except for some basic image compression on smartphones). I'm starting a research project on machine learning next semester that would require some biomedical image processing.…
rdasxy
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