How to get started in data-relation algorithms and mathematics? I am very interested in the concepts and discussions taking place here. However, I'm not entirely sure what this field of study is called or what the many branches of study are being discussed here are. It all seems to be related to finding relations and patterns in data so we can use it in a meaningful way.
As a developer, I find myself increasingly researching things like Statistical Graphing, Natural Language Processing, Bayesian filters or Probably, Bin-Packing problems, and many more. Unfortunately, I'm not sure where to go to learn these things and better contribute to the community here.
What names can I use to research and learn the topics discussed here? What would the equivalent college courses for this type of study be called?
 A: As am learning by myself too, I found actually there are too many topics in these fields to conclude into just few fixed subjects.
For self-learning, there are quite some valuable posts already existing that you can search in specific topics in Stats.SE.
Below are some of the resources I found very useful and/or interesting:
As in text related ML, Christopher Manning's Introduction to Information Retrieval is a really good first book. Free online, well written, not difficult in math.
For machine learning, Christopher Bishop's PRML is a good choice as the second book with broad cover yet in-depth theoretical explanations.
There is an on-line open course "Machine Learning" by Professor Andrew Ng from Stanford Artificial Intelligence Lab.
The Elements of Statistical Learning is one of the best in statistical learning, really nice if you want to learn the math/theory part.
I found deep learning to be a quite interesting topic in machine learning. You can watch this nice introductory video here.
