diff --git a/docker/Dockerfile b/docker/Dockerfile
new file mode 100644
index 000000000..fdac2f843
--- /dev/null
+++ b/docker/Dockerfile
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+FROM nvidia/cuda:7.5-cudnn5-devel
+
+ENV CONDA_DIR /opt/conda
+ENV PATH $CONDA_DIR/bin:$PATH
+
+RUN mkdir -p $CONDA_DIR && \
+    echo export PATH=$CONDA_DIR/bin:'$PATH' > /etc/profile.d/conda.sh && \
+    apt-get update && \
+    apt-get install -y wget git libhdf5-dev g++ graphviz && \
+    wget --quiet https://repo.continuum.io/miniconda/Miniconda3-3.9.1-Linux-x86_64.sh && \
+    echo "6c6b44acdd0bc4229377ee10d52c8ac6160c336d9cdd669db7371aa9344e1ac3 *Miniconda3-3.9.1-Linux-x86_64.sh" | sha256sum -c - && \
+    /bin/bash /Miniconda3-3.9.1-Linux-x86_64.sh -f -b -p $CONDA_DIR && \
+    rm Miniconda3-3.9.1-Linux-x86_64.sh
+
+ENV NB_USER keras
+ENV NB_UID 1000
+
+RUN useradd -m -s /bin/bash -N -u $NB_UID $NB_USER && \
+    mkdir -p $CONDA_DIR && \
+    chown keras $CONDA_DIR -R && \
+    mkdir -p /src && \
+    chown keras /src
+
+USER keras
+
+# Python
+ARG python_version=3.5.1
+ARG tensorflow_version=0.9.0rc0-cp35-cp35m
+RUN conda install -y python=${python_version} && \
+    pip install https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-${tensorflow_version}-linux_x86_64.whl && \
+    pip install git+git://github.com/Theano/Theano.git && \
+    pip install ipdb pytest pytest-cov python-coveralls coverage==3.7.1 pytest-xdist pep8 pytest-pep8 pydot_ng && \
+    conda install Pillow scikit-learn notebook pandas matplotlib nose pyyaml six h5py && \
+    pip install git+git://github.com/fchollet/keras.git && \
+    conda clean -yt
+
+ADD theanorc /home/keras/.theanorc
+
+ENV PYTHONPATH='/src/:$PYTHONPATH'
+
+WORKDIR /src
+
+EXPOSE 8888
+
+CMD jupyter notebook --port=8888 --ip=0.0.0.0
+
diff --git a/docker/Makefile b/docker/Makefile
new file mode 100644
index 000000000..acc6450a3
--- /dev/null
+++ b/docker/Makefile
@@ -0,0 +1,26 @@
+help:
+	@cat Makefile
+
+DATA?="${HOME}/Data"
+GPU?=0
+DOCKER_FILE=Dockerfile
+DOCKER=GPU=$(GPU) nvidia-docker
+BACKEND=tensorflow
+TEST=tests/
+SRC=$(shell dirname `pwd`)
+
+build:
+	docker build -t keras --build-arg python_version=3.5 -f $(DOCKER_FILE) .
+
+bash: build
+	$(DOCKER) run -it -v $(SRC):/src -v $(DATA):/data --env KERAS_BACKEND=$(BACKEND) keras bash
+
+ipython: build
+	$(DOCKER) run -it -v $(SRC):/src -v $(DATA):/data --env KERAS_BACKEND=$(BACKEND) keras ipython
+
+notebook: build
+	$(DOCKER) run -it -v $(SRC):/src -v $(DATA):/data --net=host --env KERAS_BACKEND=$(BACKEND) keras
+
+test: build
+	$(DOCKER) run -it -v $(SRC):/src -v $(DATA):/data --env KERAS_BACKEND=$(BACKEND) keras py.test $(TEST)
+
diff --git a/docker/README.md b/docker/README.md
new file mode 100644
index 000000000..d3ffd2735
--- /dev/null
+++ b/docker/README.md
@@ -0,0 +1,58 @@
+# Using Keras via Docker
+
+This directory contains `Dockerfile` to make it easy to get up and running with
+Keras via [Docker](http://www.docker.com/).
+
+## Installing Docker
+
+General installation instructions are
+[on the Docker site](https://docs.docker.com/installation/), but we give some
+quick links here:
+
+* [OSX](https://docs.docker.com/installation/mac/): [docker toolbox](https://www.docker.com/toolbox)
+* [ubuntu](https://docs.docker.com/installation/ubuntulinux/)
+
+## Running the container
+
+We are using `Makefile` to simplify docker commands within make commands.
+
+Build the container and start a jupyter notebook
+
+    $ make notebook
+
+Build the container and start an iPython shell
+
+    $ make ipython
+
+Build the container and start a bash
+
+    $ make bash
+
+For GPU support install NVidia drivers (ideally latest) and
+[nvidia-docker](https://github.com/NVIDIA/nvidia-docker). Run using
+
+    $ make notebook GPU=0 # or [ipython, bash]
+
+Switch between Theano and TensorFlow
+
+    $ make notebook BACKEND=theano
+    $ make notebook BACKEND=tensorflow
+
+Mount a volume for external data sets
+
+    $ make DATA=~/mydata
+
+Prints all make tasks
+
+    $ make help
+
+You can change Theano parameters by editing `/docker/theanorc`.
+
+
+Note: If you would have a problem running nvidia-docker you may try the old way
+we have used. But it is not recommended. If you find a bug in the nvidia-docker report
+it there please and try using the nvidia-docker as described above.
+
+    $ export CUDA_SO=$(\ls /usr/lib/x86_64-linux-gnu/libcuda.* | xargs -I{} echo '-v {}:{}')
+    $ export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
+    $ docker run -it -p 8888:8888 $CUDA_SO $DEVICES gcr.io/tensorflow/tensorflow:latest-gpu
diff --git a/docker/theanorc b/docker/theanorc
new file mode 100644
index 000000000..85592e931
--- /dev/null
+++ b/docker/theanorc
@@ -0,0 +1,5 @@
+[global]
+floatX = float32
+optimizer=None
+device = gpu
+