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Irrelevant. If you're doing anything even mildly related to ML/stat, Python is essential. It's close to impossible to replicate the eco-system that has been bu

• fmbb 2y ago
  What parts of the eco system? I never dove into it but when I spent two days at work in 2021 on a hackathon to make “something anything” with “AI” it was very hard to just google and figure things out (with no prior knowledge and no time). We did not end up using pytorch because the setup of a python toolchain that just works was very daunting and all the blogs and guides did not explain how to connect any of the pieces that make up training or a model or inference. We landed on TensorFlow with golang and completed the hackathon with a working game. Granted, we probably used five lines of python for the training and defining the network. It seems to me that Python in that case did not bring much into the picture, except the five lines we cargo culted to define the network because we did not have time to find any sort of documentation for beginners to just build something (in the time we had).
  • Ukv 2y ago
    That you were able to use Python to define and train the network in so few lines of code, with no prior knowledge and a 2-day deadline, sounds fairly successful to me. I think a hackathon will inevitably favor quick copy-pasting, gluing APIs together, and utilizing tools you're familiar with - as opposed to being a good place for beginners to build an understanding of the fundamentals.
• stevenae 2y ago
  This is not true. R shines for classical stats and ML. If you are doing deep learning, you need Python.