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Dale McDiarmid
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Merge pull request #280 from Winterflower/ml-classification-notebook
Companion Jupyter notebook for ML Classification Analytics
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## Kibana Sample Flights Data Classification Example
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Set up a local instance of Jupyter using the following instructions
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1. Set up a virtual environment called `env`
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```
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python3 -m venv env
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```
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2. Activate it
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```
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source env/bin/activate
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```
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3. Install the required dependencies for your chosen Jupyter notebook
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```
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pip install -r some-requirements-file-name.txt
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```
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4. Launch Jupyter
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```
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jupyter notebook
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```
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appnope==0.1.0
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attrs==19.3.0
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backcall==0.1.0
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bleach==3.1.0
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certifi==2019.11.28
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chardet==3.0.4
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decorator==4.4.1
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defusedxml==0.6.0
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elasticsearch==7.1.0
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entrypoints==0.3
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idna==2.8
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importlib-metadata==1.2.0
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ipykernel==5.1.3
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ipython==7.10.1
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ipython-genutils==0.2.0
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ipywidgets==7.5.1
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jedi==0.15.1
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Jinja2==2.10.3
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jsonschema==3.2.0
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jupyter==1.0.0
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jupyter-client==5.3.4
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jupyter-console==6.0.0
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jupyter-core==4.6.1
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MarkupSafe==1.1.1
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mistune==0.8.4
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more-itertools==8.0.0
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nbconvert==5.6.1
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nbformat==4.4.0
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notebook==6.0.2
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pandocfilters==1.4.2
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parso==0.5.1
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pexpect==4.7.0
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pickleshare==0.7.5
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prometheus-client==0.7.1
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prompt-toolkit==2.0.10
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ptyprocess==0.6.0
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Pygments==2.5.2
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pyrsistent==0.15.6
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python-dateutil==2.8.1
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pyzmq==18.1.1
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qtconsole==4.6.0
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requests==2.22.0
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Send2Trash==1.5.0
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six==1.13.0
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terminado==0.8.3
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testpath==0.4.4
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tornado==6.0.3
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traitlets==4.3.3
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urllib3==1.25.7
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wcwidth==0.1.7
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webencodings==0.5.1
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widgetsnbextension==3.5.1
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zipp==0.6.0

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