Installing dependencies
justheuristic opened this issue · 7 comments
Any issues concerning installation can just as well be sent here.
We assume that you have basic data science toolkit (sklearn, numpy/scipy/pandas). Basically whatever comes with default anaconda distribution.
- Anaconda: https://www.continuum.io/downloads (or simply use python with numpy/sklearn)
The majority of course assignments assignments use OpenAI gym
- Installing gym: https://github.com/openai/gym#installation
If you don't/can't install that (e.g. you use windows and installation is tricky), there's a docker container contributed to the course.
Deep learning
You will also need one of the following three stacks:
-
PyTorch:
- Installing on Linux / Mac OS: http://pytorch.org/
- Installing on windows: https://anaconda.org/peterjc123/pytorch (CPU only)
-
TensorFlow:
pip install tensorflow
pip install keras
- Detailed guide
-
Theano:
- only theano and lasagne - pick bleeding edge version
- all 3 of them
The frameworks can be easily installed on Mac OS and Linux. Windows installation is, a bit tougher, so if you don't feel like it, try using docker (e.g. kitematic gui or console on windows).
Install docker
Clone docker repo: https://hub.docker.com/r/justheuristic/practical_rl
(or just docker pull justheuristic/practical_rl
if you have docker shell)
If you want to build it yourself, use these instructions.
If you run into any trouble, feel free to post here, even if it's like "i don't know what the hell all these letters mean!!!".
One question: We'll use Python 2.7 or 3 in this course? I couldn't find that anywhere.
@LecJackS, I've commented your question in the gitter chat.
Thanks @arogozhnikov , I'll copy it here:
@LecJackS notebooks are written in the way to work in both, so whichever you prefer.
If you have no preference, then please use 2.7
The Linux "native docker" instructions in Practical_RL/tree/master/docker, in addition to needing better formatting (I think right now there is no carriage return between the two docker commands), needed the -it and -v parameters moved in front of the image name, otherwise my Ubuntu docker was giving me errors.
I'm reasonably certain that this issue can be now closed. Let's open more specific issues as needed.
Are there any solutions to the notebooks? thanks
@nikikotecha we don't publish the solutions to discourage the students who take this course in-person from cheating.
Also, please open separate issues for similar questions instead of posting them here.