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Statistical Machine Learning 1RT700

This repository is used to host the files needed for the exercise sessions and the computer lab in the course Statistical Machine Learning at Uppsala University.

Problem solving sessions

The material associated with each session is given below together with a set of recommended problems.

For each session, the material consists of the following:

Pen-and-paper class:

  • Single pdf file with problems and solutions.

Computer class:

  • Jupyter notebook with problems.
  • Direct link to run notebook in Google Colab.
  • Notebook exported to HTML with solutions.

Data used in the computer classes can be downloaded directly in the notebooks. For offline use, we recommend you download the whole repository and make the necessary changes to the notebook by commenting/uncommenting appropriate lines.

Topic Type Recommended Extra Files
1 Linear regression Pen-and-paper 1, 2, 3 4, 5 PDF
2 Linear regression Computer 1, 2, 3, 4 5 Notebook Solutions Open In Colab
3 Logistic regression, LDA, QDA, kNN Pen-and-paper 1, 2, 3, 5 4, 6, 7 PDF
4 Logistic regression, LDA, QDA, kNN Computer 1, 2, 3, 4 5 Notebook Solutions Open In Colab
5 Bias and variance, model selection, cross validation Pen-and-paper 1, 2, 3, 4 5, 6 PDF
6 Bias and variance, model selection, cross validation Computer 1, 2, 3 4 Notebook Solutions Open In Colab
7 Tree-based methods Pen-and-paper 1, 2, 3, 4 PDF
8 Tree-based methods Computer 1, 2 3 Notebook Solutions Open In Colab
9 Boosting Computer 1, 2, 3 4, 5
10 Neural networks Pen-and-paper 1, 2, 3, 4 PDF

Computer lab

For the computer lab about deep learning the following resources are available:

Topic File Links
Lab instructions instructions.pdf PDF
Introduction to PyTorch introduction.ipynb Introduction Notebook Open In Colab
One-layer NN for MNIST mnist_onelayer.ipynb MNIST Notebook Open In Colab
Image classification with VGG16 VGG16_classification.ipynb VGG16 Notebook Open In Colab

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Course material for 1RT700 Statistical Machine Learning

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