This contribution to the proceedings will present different
applications of neural networks as a powerful tool to improve the
measurement of the B0(s) oscillation frequency.  Opposite side lepton tagger
gain performance due to a better particle identification and a better
candidate selection.  The jet charge tagger uses neural networks to measure
the probability of tracks originating from B mesons and improve the
identification of jets as b-jet candidates.