This repository contains programming assigments and projects for Udacity's Deep RL Nanodegree program.
We would use dockerized env for execution the project files. The requirements stemming from udacitys repo are located here
Just update the requirements if necessary, but afterward you should also rebuild the docker-image
with docker-compose build --force-rm.
After checking out just run docker-compose up -d jupyter
and the jupyter notebook server should be accessible on your localhost on port 8888. If necessary,
you can modify the docker-compose.yml
If You are using a client with nvidia GPU, there is also a separate dockerfile and service for that.
To use it run docker-compose up -d jupyter-gpu. Nvidia driver, CUDA, nvidia-docker etc are prerequisites
to use the GPU enabled jupyter, a more detailed guide will probably follow soon.
Since I like to use an IDE (e.g. PyCharm) for debugging, also included a separate service for debugging through
docker-compose with the IDE. Just add the debug service from the compose file as project interpreter, and you
can use the IDE for debugging the code running inside the defined docker container.
The solutions for the actual exercises and project can be found in this folder.
I will add further content as I progress through the nanodegree program.