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I've heard of various different types of machine learning algorithms such as logistic regression, neural networks, naive bayes etc, and I was wondering what goes into creating a machine learning algorithm? How do they know when it is "good"? How do you create a machine learning algorithm?

Thanks

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closed as too broad by Tim, gung, dsaxton, Christoph Hanck, Sycorax Mar 4 '16 at 13:22

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

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this link might give you a quick overview: http://machinelearningmastery.com/a-tour-of-machine-learning-algorithms/

I think new machine learning algorithms are mostly created if a new type of problem occurs that somehow cannot be fixed with the existing methods. You realize they don't work as you expect them to, you get the problem, you improve the algorithm or maybe create a new one (which is extremely hard to do since most ideas have already been implemented).

If you want to USE a certain algorithm, you should first pick a programming language that suits you and then download the necessary package. Learn how to start (tutorials, try & error) and then get your results.

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  • $\begingroup$ please summarize the key points of your link in case it dies in the future $\endgroup$ – Antoine Mar 4 '16 at 13:17

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