This repository created to support https://hands-on.cloud articles:
- How to run Jupiter, Keras, Tensorflow and other ML libs in Docker
- How to build Anaconda Python Data Science Docker container
This is fully ready Docker container with:
- NumPy
- Pandas
- Sklearn
- Matplotlib
- Seaborn
- pyyaml
- h5py
- Jupyter
- Tensorflow
- Keras
- OpenCV 3
We're building this container on top of Ubuntu 20.04 Docker container (Dockerfile) and Anaconda Docker container (Dockerfile)
We'll use notebooks
forlder to store Jupyter Notebooks:
mkdir notebooks
Run Docker container with the following command:
docker run -it -p 8888:8888 -p 6006:6006 -d -v $(pwd)/notebooks:/notebooks amaksimov/python_data_science
We're using following parameters:
-p 8888:8888
to export Jupyter Web interface-p 6006:6006
to export TensorflowDashboard Web interface-d
to run Docker container in background-v notebooks:/notebooks
to mount just created notebooks folder Docker inside container