TFLearn

Slow, and rather painstaking advances in Parag Mital’s course on Kadenze and associated repo… TensorFlow really is verbose. I imagine one must be happy to have all these options when mastering the whole thing, but it does make the learning process more difficult. Another thing that comes to mind: as often happens, visual arts and music take the lion’s share in the computational arts business, and unsurprisingly Mital’s course focuses on that (although I noticed that there is a textual model hidden deep in the repo, to be studied in due course).

While looking for simpler paths of entry into the TensorFlow library (and given my current progress I’d probably stick with it rather than try and learn PyTorch or Keras), I came across another source for learning: TFLearn, a high-level library built on top of TensorFlow, meant to make access to it lighter without removing the possibility to dig deeper if need be.

The examples for text generation that I intend to work with can be found here and there.