Written for STAT 503 after reading two introductions to cluster analysis.
Cluster analysis is a type of unsupervised learning. Up until this point in STAT 503, we have just been studying supervised learning methods, so unsupervised learning is an exciting new challenge.
Written for STAT 503 after watching some videos about Weka.
These videos were a very nice introduction to the capabilities of Weka. In the first video, we learned how to classify using logistic regression, decision trees, neural networks and support vector machines using Weka.
Written for STAT 503 after watching Andrew Ng’s lectures, numbers 43-46 on neural networks.
Neural networks are something I’ve heard of before, but I’ve never really understood why exactly they were called neural networks.
Written for STAT 503 after reading this paper on model visualization by Wickham, Cook, and Hofmann.
What struck me the most about this paper was how intuitive the idea of model visualization seemed to me, yet I don’t think I’ve ever used it in a statistical modeling course.
Written for Stat 503 after reading
This paper on the housing crisis in the Bay Area, This interview with Hadley Wickham, Naomi Robbins’ blog at Forbes, Some entries on the Beautiful Data blog, and This column on variation.