A central objective of NECCTON is the construction of a new codes and algorithms to push forward the state-of-the-art of the Copernicus Marine Service in integrating numerical model simulations and new and consolidated types of observations. A list of algorithms based on machine learning and data assimilation have been developed in the tasks T4.2, T4.3 and T4.4 of the work package 4. The algorithms are shared internally and externally to the project through GitHub repositories following the guidelines described in deliverable 4.1 (Brajard et al., 2023). The codes are shared through a NECCTON common organization https://github.com/neccton-algo. The list of new algorithms includes emulators of ocean models, methods for the interpolation of satellite and sparce in situ data, methods for bias correction of model results, methods to handle zooplankton and fish data, and approaches for the assimilation of new type of observations. The codes are described in the GitHub repositories and recalled in section 3 of this document. For each algorithm, the text includes code repository link, code owner and a brief description of the code.