Jeff Dean Keynote at GTC 2015
Nvidia puts on its GPU Technology Conference (GTC) each year to highlight work being done on GPUs outside of graphics–including machine learning. Last year, Jeff Dean from Google gave one […]
Nvidia puts on its GPU Technology Conference (GTC) each year to highlight work being done on GPUs outside of graphics–including machine learning. Last year, Jeff Dean from Google gave one […]
This post is just intended to capture my notes on the PageRank algorithm as described in the Mining Massive Datasets course on Coursera. It is described in detail in chapter […]
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 […]
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 […]
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. Installation I found […]
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. […]
I thought I’d share briefly some of our team’s recent experiences in renting time on GPUs for machine learning work. You’ve probably seen that GPUs are gaining popularity for machine […]
In this post, I provide a detailed description and explanation of the Convolutional Neural Network example provided in Rasmus Berg Palm’s DeepLearnToolbox for MATLAB. His example code applies a relatively simple CNN […]
While reading through various deep learning research papers, I’ve come across the term “L2-SVM” a couple times. For example: “In our experiments we use (L2) SVM classification.” – An Analysis of Single-Layer […]
The Euclidean distance (also called the L2 distance) has many applications in machine learning, such as in K-Nearest Neighbor, K-Means Clustering, and the Gaussian kernel (which is used, for example, […]