Today, I was putting together and testing my Data Science Toolbox in Docker  which consists of the following components:

  • GUI/Environment
    – jupyter
    – python3
  • Core Libraries
    – NumPy
    – SciPy
    – Pandas
  • Visualization
    – Matplotlib
    – Seaborn
  • Machine Learning
    – SciKit-Learn
    – Keras
    – TensorFlow

It is based on the lean Alpine Linux!

Here is the version information of the installed components:

In [12]:
import sys
print(sys.version)
3.6.2 (default, Aug 29 2017, 13:56:02) 
[GCC 6.4.0]
In [11]:
print("Installed Modules:");
import pip
sorted(["%s==%s" % (i.key, i.version) for i in pip.get_installed_distributions()])
Installed Modules:
Out[11]:
['bleach==1.5.0',
 'cycler==0.10.0',
 'decorator==4.1.2',
 'entrypoints==0.2.3',
 'google-api-python-client==1.6.4',
 'html5lib==0.9999999',
 'httplib2==0.10.3',
 'ipykernel==4.6.1',
 'ipython-genutils==0.2.0',
 'ipython==6.2.0',
 'ipywidgets==7.0.1',
 'jedi==0.11.0',
 'jinja2==2.9.6',
 'jsonschema==2.6.0',
 'jupyter-client==5.1.0',
 'jupyter-console==5.2.0',
 'jupyter-core==4.3.0',
 'jupyter==1.0.0',
 'keras==2.0.8',
 'markdown==2.6.9',
 'markupsafe==1.0',
 'matplotlib==2.0.2',
 'mistune==0.7.4',
 'nbconvert==5.3.1',
 'nbformat==4.4.0',
 'nltk==3.2.5',
 'notebook==5.1.0',
 'numpy==1.13.1',
 'oauth2client==4.1.2',
 'olefile==0.43',
 'pandas==0.20.3',
 'pandocfilters==1.4.2',
 'parso==0.1.0',
 'pexpect==4.2.1',
 'pickleshare==0.7.4',
 'pillow==4.2.1',
 'pip==9.0.1',
 'prompt-toolkit==1.0.15',
 'protobuf==3.4.0',
 'ptyprocess==0.5.2',
 'pyasn1-modules==0.1.4',
 'pyasn1==0.3.6',
 'pygments==2.2.0',
 'pyparsing==2.2.0',
 'python-dateutil==2.6.1',
 'pytz==2017.2',
 'pyyaml==3.12',
 'pyzmq==16.0.2',
 'qtconsole==4.3.1',
 'rsa==3.4.2',
 'scikit-learn==0.19.0',
 'scipy==0.19.1',
 'seaborn==0.8.1',
 'setuptools==28.8.0',
 'simplegeneric==0.8.1',
 'six==1.11.0',
 'tensorflow-tensorboard==0.1.7',
 'tensorflow==1.3.0',
 'terminado==0.6',
 'testpath==0.3.1',
 'tornado==4.5.2',
 'traitlets==4.3.2',
 'uritemplate==3.0.0',
 'wcwidth==0.1.7',
 'werkzeug==0.12.2',
 'wheel==0.29.0',
 'widgetsnbextension==3.0.3']
Categories: Data Science

1 Comment

Nella Szabat · 23. March 2018 at 9:19

Excellent publish from specialist also it will probably be a fantastic know how to me and thanks very much for posting this useful data with us all.

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