On February 28, I presented at the University of Kentucky’s Mathematics Department Alumni Day. My talk contains practical advice for math students (graduate and undergraduate) to prepare for Machine Learning careers.
I’m working through Wasserman’s All of Nonparametric Statistics, a wonderful and concise tour of nonparametric techniques. What is nonparametric statistics? It is a collection of estimation techniques that make as few assumptions as possible about the distribution from which your data came. Let’s work through an example in R that’s mentioned in Chapter 3 of… Read More A Jackknife Example
In the past, I wrote frequently about quadratic programming especially in R, for example here and here. It’s been a while and at least one great new library has emerged since my last post on quadratic programming — OSQP. OSQP introduces a new technique called operator splitting which offers significant performance improvements over standard interior… Read More Sparse quadratic programming with osqp
So you’ve filled an S3 bucket with hundreds of millions of objects and now, for one reason or another, you need to copy that data into another S3 bucket. How do you do that efficiently? If you’ve worked with S3 for awhile, you’ve probably seen how painfully slow it is to list all of the… Read More Copying lots of data between S3 buckets
Reading through papers on the Word2vec skip-gram model, I found myself confused on a fairly uninteresting point in the mechanics of the output layer. What was never made explicit enough (at least to me) is that the output layer returns the exact same output distribution for each context. To see why this must be true,… Read More Word2Vec: Skip-Gram Feedforward Architecture