In summary, ANNs are powerful instrument of ML for developing quantitative regression models and can be applied for solving a lot of tasks. The main advantage is that only data are required for building models, and, thus, it obviates the need to suggest (guess) reaction mechanism, rate-determining stage etc. in the case of kinetic modelling. However, one of the known disadvantages in applying neural networks is the requirement of a lot of data for training . This so far limits the usage of ANNs in the case of small data sets which are typically available for experiment-driven development of kinetic models.