This post provides some overview and explanation of NVIDIA’s provided sample project ‘matrixMulCUBLAS’ for super-fast matrix multiplication with cuBLAS. The example can be a little confusing, and I think it warrants some explanation.

A number of people have asked me, in response to my tutorial on Radial Basis Function Networks (RBFNs) for classification, about how you would apply an RBFN to function approximation or regression (and for Matlab code to do this, which you can find at the end of the post).

I’ve spent some time playing with the document clustering example in scikit-learn and I thought I’d share some of my results and insights here for anyone interested.

In this post, I’m providing a brief tutorial, along with some example Python code, for applying the MinHash algorithm to compare a large number of documents to one another efficiently.