I’ve been learning machine learning from uni, but I haven’t done
as much practical stuff as I’d like so I decided to do some in the
Most of the books I’ve looked at (Deep learning pipeline). These
are pretty recent (2018ish) but mostly seem to either feature
tensorflow 1, need a previous version of keras to be compatible,
etc etc. Things like the Mnist dataset are also in different forms
across different versions.
For tensorflow I’ve been just using
To just keep compatibility with tensorflow 1 so I can follow
along with the examples better, but should I just try to find
something more recent than 2018?
One of the tutorials also wanted me to run all code on an ubuntu
google cloud machine?
Are there any super good tensorflow books that are up to date
that you’d recommend? I’ve literally just been searching for deep
learning at the university online library.
It seems kinda dumb that the way the framework operates changes
so much in such a short period of time. I’m willing to put time in,
but I don’t want to go through a 500 page book to realize that
everything is now obsolete. Also how the hell do people working in
the industry deal with this, when half of the code they’ve written
is now not compatible with the main version.