Applied Machine Learning - Week 7

Monday 7th of June (morning):
Lectures: GPU accelerated data analysis - Rapids (Mads Kristensen, Nvidia - formerly NBI).

Zoom:Link to lecture (Recorded!).
     Recording in Lecture video (127 MB).

Exercise: Work on final project.

Wednesday 9th of June (morning):
Lectures: T-distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP) (TP).
     ML cases and Industry Ideas (TP).

Zoom:Link to lecture (Recorded!).
     Recording in Lecture video (117 MB).

Exercise: Work on final project.

Wednesday 9th of June (afternoon):
Lectures: Results and Scores on Small Project (TP and CJ).
Link to descriptions of ML setup for most performant algorithms (this year all LightGBM!):
     Classification 1: Mia-Louise Nielsen (0.1330)
     Classification 2: Kasper Nielsen (0.1361)
     Classification 3: Jonathan Greve (0.1367)
     Regression 1: Clara Heine (7916.6)
     Regression 2: Mia-Louise Nielsen (7952.6)
     Regression 3: Arnau Morancho Tarda (7958.4)

Zoom:Link to lecture (Recorded!).
     Recording in Lecture video (172 MB).

Exercise: Work on final project.

Last updated: 9th of June 2021 by Troels Petersen.