Trax is a horrible choice for an online course at present

Trax is not bad though nowhere as nice as keras or pytorch specially for those with a decent programming background. Even the basic CPU version is a nightmare to install/upgrade. Combine that with lack of documentation and community support (which takes a while), this is a really bad choice for an online course. It is not sufficient for a library to be new or cool, there are many other things to consider while choosing a library. Coursera has clearly missed the mark here and made the learning experience unnecessarily bad.

Thank you for your feedback, @Abhijat.Vatsyayan. It is appreciated. I shall take this back to the team.

I completely agree. For me Trax is nowhere as user-friendly or intuitive as the other two (Keras, PyTorch) and the reduction of boilerplate from Pytorch gets replaced with succinct but cryptic syntax which is neither well-documented in the official documentation nor explained as part of these videos. Overall I find it inappropriate to push an experimental and relatively new tool such as Trax part of a MOOC.

I don’t think you should pin this on Coursera; owns this decision and my assumption/explanation is as simple as ‘The Google force is strong with this one.’

I’m more annoyed by the fact that trax isn’t widely supported by hardware/OS platforms than the syntax or usage of the library itself. Means I can’t run any of the exercises from the class at home without rewriting everything. PITA.

1 Like

Agreed, I did not take into account how Coursera works. has completely missed the mark here.

I totally agree and found Trax to be nowhere as user-friendly as Keras. TBH, I had never even heard of it before. Personally, I prefer the functional API in the latter, which allows for a great deal of customization, especially in constructing complex model architectures.
Please consider this @Mubsi.

Hi @Anivader,

Your feedback has been noted.


Agreed. Trax is no longer an active project. There were less than two dozen commits in 2022 and as of July 1, only two commits for all of 2023. I just finished the Deep Learning specialization and was beginning to get up to speed with Tensorflow. I was hoping to continue learning with this second specialization. I’m deeply frustrated to be forced to use a framework that I’m probably never going to see again. This is the first time I’ve been truly disappointed with