Using pre-trained deep learning models like ResNet, Inception, and VGG is easier than ever, but there are implementation details you need to be careful with to avoid subpar performance and errors.

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Put together this list of implementation details to be cautious of — curious to see if I’m missing anything or if other folks have had similar experiences with discrepancies in performance?

https://medium.com/comet-ml/approach-pre-trained-deep-learning-models-with-caution-9f0ff739010c