Applied Machine Learning - Week 4

Monday the 13th - Friday the 17th of May 2024

Final project groups: Click here to register your group (don't worry - not final).


Monday 13th of May (afternoon):
Lectures: Auto-Encoder and anomaly detection (Inar Timiryasov).

Exercise: The exercise is about classifying digits i.e. the MNIST data, but this time in an unsupervised manner with an autoencoder.
     Following this we will repeat the exercise, this time with a Variational AutoEncoder.
     Potentially also useful for anomaly detection in these images.


Wednesday 15th of May (morning):
Lectures: Final projects kickoff. Introducing Potential Datasets and Projects (TP).

Exercise: The exercise simply to get set up for the final project. It is highly advantages to get hold of your data (or part of it) before this.
     Things to consider are data (have it or get it right away), group, goals of analysis, and methods.
     During these exercises you should aim to settle your final project groups and discuss what data to work on.


Wednesday 15th of May (afternoon):
Lectures: Further work on Unsupervised Learning: Dimensionality reduction (and related cleaning of data).

Exercise: The exercise starts with an introduction to dimensionality reduction.
     The "real" exercise is (preprocessing and) applying dimensionality reduction to the Cosmos2015 data.
     The analysis can also include the Swift Properties and Swift Gamma Ray Bursts datasets.

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Last updated: 12th of May 2024 by Troels Petersen.