I am running a neural network for image classification using the Matlab deep learning toolbox. The algorithm contains three instances of convolution2dLayer, and it trains using TrainNetwork. If I run the exact same algorithm (identical code) on a different computer, my algorithm returns vastly different results: one computer yields a very high accuracy, around 99%, while the other never learns at all (the learning curve never increases above 50%). The only difference between the two computers is the Matlab version. The 99% accurate computer is on Matlab 2019a (Deep Learning Toolbox, version 12.1), while the 50% accurate computer is on Matlab 2019b (Deep Learning Toolbox, version 13.0). Is it expected that these two versions, which are so close together, would return such different results? I also find it surprising that the older version is better, but as machine learning is a blackbox, perhaps this is entirely possible? Are there any other reasons the results could be so different?