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Machine Learning Workbook

This online workbook, created by Thomas Stevenson, will introduce the basics of Machine Learning and how it can be exploited in an experimental physics context. Experience with python is required, however no knowledge of ML is necessary. Warning: it may take a long time to load the workbook and associated repositories! A preview is available by clicking on the image. 

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The notebook uses real proton-proton collision data from the ATLAS experiment at CERN to explore some hands-on examples, implementing some of the most commonly used Machine Learning techniques and exploring the potential uses of Machine Learning. 

This presentation by Caley Yardley is designed to accompany the workbook, and provide additional explanations for concepts found inside. The slides in the video can be downloaded through the link below, so you can go through them at your own pace. 

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