Sources:
https://www.statlearning.com/
http://ciml.info/
Slides
Introduction slides
Supervised Learning slides
Model selection slides
Unsupervised Learning slides
Review materials:
Gradient
MLE & MAP estimation
Python Notebooks
knn-classification®ression
Decision_trees(basics)
cross_validation_concept(for knn)
ROC_illustration (for DT)
Post Prunning Decision Trees
Boosting with Adaboost
Bagging with RandomForest
One-Class SVM
Visualization of nonlinear transform in SVM
SVM parameters analysis
PCA
Homeworks
HW1 (deadline: 5th April)
HW2 (deadline: 19th May)
Send homeworks to ds.kntu.homeworks@gmail.com
Presentations Schedules:
4 خرداد: صدفی، پاکدامن
6 خرداد: برزگر، آقایی
11 خرداد: قمی، خیامه
13 خرداد: محمدی، امینی