Submitted by ContributionWild5778 t3_10im3z3 in deeplearning

Hello, My fellow deep learning partners. I am in a dilemma where I cannot choose what framework I should go forward to learn. From theory perspective if I take one more course or blog on how deep learning models learn, I will take a jump from 5 story building.

I want a good practical practice (if you have any course/book for that please suggest). I read somewhere in this blog that tensorflow will be reaching EOL soon. Shall I go with pytorch ?

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OutrageousSundae8270 t1_j5g1x5q wrote

Um, I don't think TF2 is reaching EOL anytime soon? Do you have any other sources besides a blog post regarding this?

Try both frameworks and pick the one that is more intuitive for you, you can always circle back and learn the other if you need anyway.

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OutrageousSundae8270 t1_j5g4152 wrote

One of the posters in that thread says "Google always struggled to build a long lasting ecosystems for their products", I don't even see how that is relevant anymore since TF has been open sourced and is not necessarily maintained by Google anymore.

PyTorch is more popular I concede that, but I don't think the people responsible for maintaining TensorFlow are going to shut up shop just because PyTorch is modestly more popular.

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OutrageousSundae8270 t1_j5g51tx wrote

I'm know the TensorFlow API really well considering I've been using it for about 2 years now.

I've used PyTorch before as well, its really not hard to learn the other once you're good at one of them.

PyTorch is a little more verbose than TensorFlow , e.g. TensorFlow has a default training loop that can be started by invoking the fit method where as in PyTorch you write the training loop yourself regardless, you always have to explicitly call methods for AD/Back propagation as well in PyTorch.

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