GLM: exercises, correction
Day 1: R
Day 2: R, R - exercises
Day 4: R (am)
Day 1: R, pdf solution part 2, pdf solution part 3
Day 2: R, pdf solution regression-correlation
Day 3: R, R - NN, pdf solution clustering
Day 4: R (am), R (pm), R - NN, pdf solution clustering, slides decision tree random forest - part 1, slides decision tree random forest - part 2, slides decision tree random forest - part 3, practicals decision tree random forest (html), practicals decision tree random forest (pdf), practicals NN (html), practicals NN (pdf), solution (cheese dataset)
Day 3: R
introduction (R) slides Machine Learning
slides (part 1) slides (part 2) best practices segmentation preprocessing (R) best practices segmentation (R) best practices titanic (R) best practices titanic correction (R)
Numpy introduction: html, ipynb
Playing with images filters: html, ipynb
Segmenting cell images (fluorescent microscopy): html, ipynb
Subcellular location classification: html, ipynb
introduction: slides
auotoencoders: slides, exercises: pdf/html/ipynb
CNNs: slides, exercises: pdfhtml/ipynb
RNNs: slides