1. A computer-implemented method for layered training of machine-learning architectures, the method implemented by a training computing device including a processor coupled to a memory, the method comprising: receiving a plurality of data elements wherein each data element is associated with a timestamp determining a training window for each model layer of a layered stack of model layers; determining a plurality of training data elements for each training window by identifying the data elements with timestamps corresponding to each of the training windows; identifying a previous checkpoint for each model layer if the previous checkpoint for each model layer exists, wherein the previous checkpoint for each model layer is generated by a parent model layer; training each model layer with the determined training data elements for each model layer and the identified previous checkpoint, if any, for each model layer; generating a plurality of current checkpoints, wherein each current checkpoint of the plurality of current checkpoints is associated with a model layer; and; storing the plurality of current checkpoints at the memory.