Be the first to like this
The workshop will illustrate a number of techniques for data modelling that help us extend our small data capabilities to the world of big data: sampling, resampling, parallelization where possible, etc. We will leverage the functional architecture of R and its statistical analysis prowess in small data environments using the mapreduce technique embedded in Hadoop to tackle large data analysis problems. Particular attention will be paid to the ubiquitous --but non-scalable-- logistic regression technique and its big data alternatives.
Clipping is a handy way to collect important slides you want to go back to later.