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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