# I - Multivariate Classification and Machine Learning in HEP

- Institution: CERN
- Department: inverted CSC
- Speaker: Thomas KECK
- Year: 2016
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3002890)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Traditional multivariate methods for classification (Stochastic Gradient Boosted Decision Trees and Multi-Layer Perceptrons) are explained in theory and practise using examples from HEP. General aspects of multivariate classification are discussed, in particular different regularisation techniques. Afterwards, data-driven techniques are introduced and compared to MC-based methods..

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## Lectures

1. [I - Multivariate Classification and Machine Learning in HEP](https://invisiblenetwork.ai/learn/cern/3002890/5acc0eb51325), 1 h 5 min (CERN's player)