This Machine Learning and b-tagging workshop targets improvements in b-jet identification, including its basic impact parameter and vertex reconstruction algorithms, which can be gained from ML tools such as deep learning, sequence learning and domain adaptation techniques. Within ATLAS, modern ML techniques have begun to be studied for b-tagging but have yet to be fully understood and exploited. 

The workshop will introduce modern ML and b-jet identification algorithms to participants through talks and tutorials, while most of the workshop time will be dedicated to working on projects proposed by participants or meeting organizers. The may include the use of Recurrent Neural Networks and sequence learning algorithms for impact-parameter or secondary/tertiary vertexing algorithms, integration of new ML techniques into high-level b-taggin algorithms like MV2 and DL1, mitigating systematics of the high-level tagger at training time, or the development of new double b-tagging algorithms.