According to PyPI downloads and user surveys (like the yearly StackOverflow survey) the two main frameworks are TensorFlow and PyTorch for Deep Learning, and Scikit-Learn for classical ML.

See: https://survey.stackoverflow.co/2023/#technology

* TensorFlow: 9.53% usage among all devs

* Scikit Learn: 9.43%

* PyTorch: 8.75%

Every time some survey pops up, TF somehow looks still relevant while I know noone who uses it or even considers using it unless they are new to DL field. How much of TF here is v2.0?:)

Pytorch itself, or abstractions built on top such as Huggingface

Would you use Keras 3.0 for anything?

Well... some 4 years ago I got a non trivial time series forecasting tool into production, built on Keras. The experience was pretty good, there was nothing that annoyed me too much.

However, as the comments here show, the mindshare and community momentum seems to have shifted totally to Torch.

Especially considering that it's transformers everywhere, right now, and there's just so much premade stuff built on top of pytorch, I'd probably stick with that. At least out of pragmatism such as the ease of hiring people with torch experience.

The transparent Numpy experience seems nice, keras was the first thing I ever built real NNs with, all said it's never been bad to me but... to conclude, no.

We use exclusively PyTorch at work both for CV and NLP tasks and this is the standard nowadays. Keras was cool 5 years ago (last time I checked it) but it somewhat quickly faded due to TF.