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I was surprised when browsing PaperSpace.com (a gpu host for ML training) that Fast.AI is now considered a "legacy" software? I've built a few small classifiers / ML projects but not really enough to really branch out of an intermediate tutorial.

With how quickly these frameworks change it's overwhelming to keep pace! Anyone have advice for solid frameworks that can reasonably leverage GPU's without too much heavy lifting?



They must be talking about fast ai version 1. Version 2 is used everywhere now and development is on-going as usual.


Keras is integrated into TensorFlow and it's as solid and easy as it gets if you need a high level API for deep learning. If you need to write your own modules PyTorch is probably a better choice.




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