This is a modern environment for building deep learning applications. It has the latest stable versions of the most common tools and frameworks that you're likely to need.
Keep in mind that this image is big (3GB+). I considered dropping a few tools or creating different images with different toolsets, but I think that'll waste everyone's time. If you're doing deep learning then you probably have a lot of disk space anyway, and you're likely to prefer saving time over disk space.
- Ubuntu 16.04 LTS
- Python 3.5.2
- Tensorflow 1.2.1
- OpenCV 3.2
- Jupyter Notebook
- Numpy, Scipy, Scikit Learn, Scikit Image, Pandas, Matplotlib, Pillow
- Caffe
- Keras 2.0.6
- Java JDK
TODO:
- Torch
- GPU/CUDA
If you need to run older models that require Python 2.7 or OpenCV 2.4 then I'd recommend Sai's docker image . I use it in addition to this image in my daily work.
If you haven't yet, start by installing Docker. Then run this command at your terminal and it will open a bash prompt inside the container.
docker run -it -p 8888:8888 -p 6006:6006 -v ~/:/host waleedka/modern-deep-learning
Note the -v option. It maps your user directory (~/) to /host in the container. Change it if needed. The two -p options expose the ports used by Jupyter Notebook and Tensorboard respectively.