Machine learning techniques for heavy flavour identification

Reliable and performant heavy flavour identification is of prime importance for the physics program of the CMS experiment. During the last years the CMS collaboration has dedicated a considerable effort to improve and expand its capabilities in this sector by applying several machine learning techniques well established in industry, but still experimental in HEP. The poster will focus on a selection of these techniques and describe the implementation details as well as the resulting gains.