Practical examples of using machine learning algorithms
I'm just getting started with machine learning and am currently taking Andrew Ng's course on Coursera. I will take the course but lost a little. It will make learning all these algorithms / theories a lot rewarding if I can see some use cases for them.
For example, the first topic I read is gradient descent followed by linear regression and logistic regression. Are they used directly in practice or are there other algorithms like k-means and kernel density? I think I am trying to get examples of real projects (software development, data mining). Can anyone suggest a post that might have some explanation on the use of any machine learning algorithm (s)? This will be very helpful.
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NO FREE LUNCH THEOREM states that if Algorithm A beats Algorithm B for some problem, then, to put it mildly, there must be exactly the same number of other problems where Algorithm B is superior . Thus, it is difficult to associate an algorithm with a specific use case.
If you are only looking for use cases where you can use machine learning algorithms visit https://www.kaggle.com/wiki/DataScienceUseCases
Update: Just now, I came across http://pkghosh.wordpress.com . (use cases with algorithms)
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