As you have probably learned by now, training deep learning models can take long times: hours and maybe days, based on how complex the model and how large your dataset.
Sometimes it may not be practical to perform the training in one session.
Power failures, machine becoming unresponsive, OS errors, unplanned reboots, or Windows updates may lead you to lose hours if not days of effort.
How can we mitigate that risk?
One way is to increase the speed of the model training.
Using Multithreading to Increase the Training Speed
When we used the data generators with ...
