Tag: classification

Object detection and tracking in Python

Over six months ago I decided to embark on a learning journey of image analysis using Python. After carefully reviewing various options I took a two-course offer from OpenCV.org for about US$479, chiefly because of i) the pivotal role of OpenCV as an open-source toolkit in computer vision, ii) the relevance of the course modules, and iii) the vast … Continue reading Object detection and tracking in Python →

Audio classification in R

Visiting Berlin in December 2013, some friends and I spent one evening at the White Trash, a rockabilly-vibe bar decorated with hanging skeletons and a couple of conspicuous portraits of Ian "Lemmy", the late frontman of Motörhead. Incidentally, I remember trying to guess what song was playing at a certain moment when a friend opened Shazam from … Continue reading Audio classification in R →

Convolutional Neural Networks in R

Last time I promised to cover the graph-guided fused LASSO (GFLASSO) in a subsequent post. In the meantime, I wrote a GFLASSO R tutorial for DataCamp that you can freely access here, so give it a try! The plan here is to experiment with convolutional neural networks (CNNs), a form of deep learning. CNNs underlie … Continue reading Convolutional Neural Networks in R →

Partial least squares in R

My last entry introduces principal component analysis (PCA), one of many unsupervised learning tools. I concluded the post with a demonstration of principal component regression (PCR), which essentially is a ordinary least squares (OLS) fit using the first $latex k &s=1$ principal components (PCs) from the predictors. This brings about many advantages: There is virtually no … Continue reading Partial least squares in R →