## Courses given by Magda Gregorova

### Module 6c: Data science I - Introduction to machine learning (spring 2019)

Part 1: Mathematical prerequisites

- Intro math quiz
- 1 Functions
- 2 Basic classes of functions
- HW1 Functions
- 3 Sequences and series
- HW2 - Functions2
- 4 Limits
- 5 Derivatives
- HW3 - Derivatives
- 6 Integrals
- 7 Multivariate functions
- G1 Graph links

Part 2: Probability review

Part 3: Introduction to machine learning

### HEG: Informatique de gestion

#### Analyse du SI d'entreprise 2 (spring 2019)

### HEG: Économie d'entreprise

#### Valorisation du système d’information - Datamining (autumn 2018)

### Module 7d: Data science II - Selected topics in ML (autumn 2019)

The lecture notes are written by the students following the course. Thanks to them all for preparing these and allowing to make them public.

L1: Basics of probability theory (sets, probability axioms and properties, random variable, density and mass functions, expectation, variance)

scribe: Alex, helper: Lucas

P1: Expected number of coin flips code

scribe: Flavio, helper: Loic

L2: Multiple random variables (joint, marginal, conditional, Bayes rule, independence, covariance, correlation)

scribe: Loic, helper: Lucas

W2: Expectation, variance, joint, marginal, conditional probability

P2: Simpson's paradox

scribe: Alex, helper: Flavio

L3: Parametric distribution families, categorical - Bernoulli, binomial, uniform, categorical

scribe: Flavio, helper: Loic

P3: Conditional independence

scribe: Lucas, helper: Alex

L4: Gaussian, uniform continuous distribution, likelihood, maximum likelihood estimation

scribe: Lucas, helper: Flavio

W4: Likelihood jupyter notebooks

P4: Density estimation of salaries of basketball players

scribe: Loic, helper: Alex

L5: Clustering - k-means

scribe: Alex, helper: Loic

P5: Distance / proximity measures

scribe: Flavio, helper: Lucas

L6: Clustering - agglomerative hierarchical, DBSCAN, Gaussian mixture (EM)

scribe: Flavio, helper: Alex

P6: Expectation maximization for Gaussian mixture - jupyter notebook

scribe: Lucas, helper: Loic