Where to start Machine Learning?

Question

I've recently stumbled upon machine learning, generating user recommendations based on user data, generating text teaser based on an article. Although there are tons of framework that does this(Apache Mahout, Duine framework and more) I wanted to know the core principles, core algorithms of machine learning and in the future implement my own implementation of machine learning.

Where do I actually start learning Machine Learning as its basics or Machine Learning starting with concepts then to implementation? Although I have an weak to average math skills(I think that this will not hurt? If So what branches of mathematics should I study before Jumping to Machine Learning?)

Note that this is not related to my academics rather I want to learn this as an independent researcher and I am quite fascinated how machine learning works

Answer 1

You can start machine learning from Coursera Machine Learning

Answer 2

Try to read Hastie, Tishirani, Friedman "Elements of Statistical Learning". It is a nice book. If you are specifically interested in unsupervised learning, then try the quite new Kogan "Introduction to Clustering Large and High Dimensional Data": algorithms are explicitly given.

Answer 3

If you need some ideas for practical projects to immerse yourself into machine learning, you might be interested in looking at Programming Collective Intelligence by Toby Segeran.

Answer 4

In addition to great resources already mentioned, I highly recommend Kevin Murphy's book: "Machine Learning: A Probabilistic Perspective".

For implementations of machine learning algorithms, have a look at:

• https://github.com/probml/pmtk3
• https://github.com/PRML/PRMLT

Answer 5

If you really like to learn ML Algos in depth and from the scratch and want to try to implement them yourself, so you can learn and understand them better, I recommend Cornel University ML course.

For me this is thus far the best course I've ever seen on ML.