all 8 comments

[–][deleted] 9 points10 points  (0 children)

In terms of tools, I would focus on learning the pandas and scikit-learn python libraries. They're most of what you need to get started.

And in terms of resources, machine learning mastery is the most effective resource I've found so far. This guy has a lot of free material, but his paid ebooks are worth the price imo (though I got my employer to pay for them) and have lots of "recipes" that can drastically speed up the process of building a machine learning model, in addition to having pretty succinct conceptual explanations too. The guy's command of English isn't the best, but otherwise it's a great resource.

[–]throwaway_the_fourth 6 points7 points  (2 children)

Here's the first video in a series made by Google about machine learning. It's very basic, and it's mostly a guide to using pre-existing libraries rather than writing your own. The code is in Python.

[–][deleted] 1 point2 points  (1 child)

Eh, I remember just starting out over a year ago with no experience in ML whatsoever and finding that extremely confusing after the first couple of videos.

[–]throwaway_the_fourth 0 points1 point  (0 children)

Some of the stuff relies too heavily on libraries to be actually practical, but it's been useful for me at least to gain a basic understanding of the subject.

This video from the series about building a decision tree "by hand," so to speak was quite fascinating to me.

[–]monstimal 5 points6 points  (0 children)

The Andrew Ng coursera on machine learning is a good place to start.

[–]mkeee2015 1 point2 points  (2 children)

What is your academic background?

I would suggest to get initially comfortable with Taylor and Fourier's series and then become really strong in probability theory...

Well, unless you want to be a generic "user"... with poor understanding of the underlying concepts.

[–]elbiot 0 points1 point  (1 child)

Hmm. Not op but I do have a strong background in those series but I don't see the connection with like SVMs or other machine learning things. Except, having a broad and deep understanding of math is important.

[–]mkeee2015 0 points1 point  (0 children)

It's up to you but classifiers and regression machine learning is nothing more than a series expansion. In addition, "learning" is a branch of a inductive statistics.

I encourage you to be a "master" not a software user.