# Reusing ML tools and approaches for HEP data analysis

- Institution: CERN
- Department: LPCC Workshops
- Speaker: Andrey USTYUZHANIN
- Year: 2015
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3002306)
- 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)

In my talk I'm going to give an overview of the ML tools/services Yandex School of Data Analysis (YSDA) team has developed. In particular I will focus on approaches that our team has developed during collaboration with LHCb on HEP data analysis (uGB+FL, GB-reweighting). Each approach is implemented within hep_ml Python package. To get acquainted with this tool you can install it right away in your environment or experiment with it within Reproducible Experiment Platform. I will give initial guidance how you can get started playing with it..

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## Lectures

1. [Reusing ML tools and approaches for HEP data analysis](https://invisiblenetwork.ai/learn/cern/3002306/b8128bb4dba8), 43 min (CERN's player)