Lectures

See the table below for which sections of the coursebook Links to an external site. to read each week.

	Lecture	Lecturer	Reading	Warm-up videos	Slides	Recording and discussion forum
1.	Introduction and math basics	JS	1, 2.1	3 min Links to an external site. 5 min Links to an external site.	pdf Download pdf	Lecture 1
-	Introduction to Python	JS	Python notebook Links to an external site. Google Colab Links to an external site.	Python crash course Links to an external site.	pdf Download pdf	Python lecture
2.	Linear regression and regularization	TS	3.1, 5.3, 3.A	9 min Links to an external site. 1 min Links to an external site.	pdf Download pdf notes	Lecture 2
3.	Logistic regression	TS	3.2, 3.3, 4.5	3 min Links to an external site. 15 min Links to an external site.	pdf Download pdf notes	Lecture 3
4.	LDA, QDA, k-NN	SM	10.1, 2.2	15 min Links to an external site. 5 min Links to an external site.	pdf Download pdf notes Download notes	Lecture 4
5.	Bias-variance tradeoff, cross-validation	SM	4.1-4.4	6 min Links to an external site. 3 min Links to an external site.	pdf Download pdf notes Download notes	Lecture 5
6.	Tree-based methods, bagging	JS	2.3, 7.1, 7.2	10 min Links to an external site. 3 min Links to an external site.	pdf Download pdf	Lecture 6
7.	Boosting	JS	7.3, (5.2), (7.4)	2 min Links to an external site. 5 min Links to an external site.	pdf Download pdf notes Download notes	Lecture 7
8.	Deep learning part 1	NW	6.1, "Logistic regression for more than two classes" in 3.2	19 min Links to an external site.	pdf Download pdf notes Download notes demo Links to an external site.	Lecture 8
9.	Deep learning part 2	NW	6.2-6.3, 5.4-5.5, (skip "Backpropagation" in 6.2)	21 min Links to an external site.	pdf Download pdf notes Download notes	Lecture 9
10.	Summary and guest lecture	JS			pdf Download pdf	Lecture 10

JS = Jens Sjölund
TS = Thomas Schön
SM = Sebastian Mair
NW = Niklas Wahlström