ContentsΒΆ
In this course, we will cover basic concepts of statistical learning and explore their usage in a neuroscientific context.
- Exercise I: Exploratory Data Analysis (EDA)
- Exercise II: k-Nearest Neighbors (k-NN)
- Exercise III: Linear Regression
- Exercise IV: Logistic Regression
- Exercise V: Regularization
- Exercise VI: Revisiting Linear and Logistic Regression
- Exercise VII: Decision Trees and Random Forests
- Exercise VIII: K-Means Clustering and PCA
- Exercise IX: The Haxby Experiment (2001)
- Resources