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https://github.com/maxvfischer/tdde01

TDDE01 - Machine Learning, Linköping university
https://github.com/maxvfischer/tdde01

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TDDE01 - Machine Learning, Linköping university

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# TDDE01
TDDE01 - Maskininlärning | Linköpings university

## Lab 1 contains
* Spam filter done with k-nearest neighbor
* Maximum likelihood
* Feature selection in linear regression by using own implementet k-fold CV
* Polynomial regression models
* Akaike information criterion
* Ridge regression
* LASSO regression

## Lab 2 contains
* Decision trees (Gini and Deviance) to predict whether or not a new customer is likely to pay back the loan.
* Regression trees
* Confidence and prediction bands
* Principle Component Analysis (PCA) to find the features that explains the data most
* Independent Component Analysis (ICA)

## Lab 3 contains
* Sum of three gaussian kernels to forcast temperatures for a date and place in Sweden
* Train a neural network to learn the trigonometric sine function