FastestLearner t1_j630p88 wrote on January 27, 2023 at 10:20 AM

The thing with me is that I started with TensorFlow v1 back when PyTorch wasn’t even in the race, and because of the constant breaking changes to the TensorFlow API and cryptic error messages, my experience was hellish TBH. Even getting support from stackoverflow was messed up because people would be posting solutions for different API versions. Then PyTorch got released and boy was it the savior I needed. It literally saved me hundreds of hours of debugging (and possibly from brain hemorrhage too). Compared to the burning hell TF1 was, PT was like coding on a serene beach. And then TensorFlow v2 came out with eager execution, that promised PyTorch way of doing things. But then the question is, why switch if it is the same as PyTorch? And so I didn’t.

I’m coming from a research point of view. If I was coming from a production POV, things could’ve been different.

RelevantDiscussion44 t1_j6527r6 wrote on January 27, 2023 at 7:38 PM

Which one would you recommend a beginner to put time in to learn? Which one is more practical and worth putting time in?

And which one is more frequently used in the market?

FastestLearner t1_j677lru wrote on January 28, 2023 at 5:08 AM

For an absolute beginner, definitely PyTorch is what I would recommend. It’s like an extension of numpy.

Both frameworks are extremely matured and will get the job done no matter what you throw at it (I don’t get what you mean by practicality).

For industry purposes, if you have a particular company in mind, then check which framework they use (ask some employee on LinkedIn) and learn that framework (some companies still have their codebases in TF1, they never updated). If you are in the market for a job hunt, then having both on your CV will give you the best chance.