@vpj The only drawback I see is that much of the implementation is abstracted by your helper libraries. Not everyone wants to add an extra dependency layer. Otherwise the walkthroughs are super helpful.
Since the backbone of the implementation is packed away in the library import, I felt it didn't quite show the code & variable interaction well enough.
Don't get me wrong. It is useful & concise like you mentioned. But your target audience is beginners & adopters, and it makes it no different from another framework such as Fastai (I have major gripes with them. It has a much bottled-in experience)
To be true to walkthroughs, please consider designing helper functions rather than using your framework. Admittedly it may not be as beautiful, but eventually your users will be more appreciative of the extra mile you go into making things transparent & similar to PyTorch docs.
Your notebooks are very useful, thank you! May I suggest making their background white, or the color text less saturated? The keywords, function names etc. are very difficult to read, I have to paste the code in another editor.
You probably won't notice a difference unless you have allergies, or there's some other issue causing abnormally high amounts of VOCs to be in the air (such as mold or dust)
Depends on what sort of RL you are doing. If you are trying to train agents to play small games with vision the agent will need a small cnn to process images. This will need a gpu and what you have should be enough.
I was training on atari for a while with 1080ti. The games run on the cpu so you need a decent cpu as well.
