https://github.com/ceteri/nbtransom

Machines and people collaborating together through Jupyter notebooks.
https://github.com/ceteri/nbtransom

active-learning collaborative-documents human-in-the-loop jupyter-notebook machine-learning pipelines python

Last synced: 6 days ago
JSON representation

Machines and people collaborating together through Jupyter notebooks.

• Host: GitHub
• URL: https://github.com/ceteri/nbtransom
• Owner: ceteri
• License: apache-2.0
• Created: 2017-05-21T01:09:07.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-08-24T12:29:41.000Z (about 7 years ago)
• Last Synced: 2024-10-26T23:40:00.306Z (19 days ago)
• Topics: active-learning, collaborative-documents, human-in-the-loop, jupyter-notebook, machine-learning, pipelines, python
• Language: Python
• Homepage:
• Size: 13.7 KB
• Stars: 18
• Watchers: 4
• Forks: 5
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • Changelog: changelog.txt
  • License: LICENSE

Awesome Lists containing this project

README

        
Active Learning with Jupyter Notebooks

======================================

This is a Python 3 library to read/write cells programmatically in

`Jupyter notebooks `_ which anticipates upcoming

`collaborative `_

features in Jupyter.

We use this at `O'Reilly Media `_ for

notebooks used to manage machine learning pipelines.

That is to say, *machines and people collaborate on documents*, 

implementing a "human-in-the-loop" design pattern:

-  people adjust parameters for the ML pipelines

-  machines write structured "logs" during ML modeling/evaluation

-  people run ``jupyter notebook`` via SSH tunnel for remote access

For more info about use cases for this library and *active learning* 

in general, see the `JupyterCon 2017 `_ talk

`Humans in the loop `_

Example Usage

-------------

The following script generates a Jupyter notebook in the ``test.ipynb``

file, then runs it:

::

    python test.py

    jupyter notebook

Then launch the ``test.ipynb`` notebook and from the ``Cells`` menu

select ``Run All`` to view results.

NB: whenever you use the ``put_df()`` function to store data as a 

`Pandas dataframe `_

be sure to include ``import pandas as pd`` at some earlier point in

the notebook.

Dependencies and Installation

-----------------------------

This code has dependencies on:

-  `nbformat `_

-  `pandas `_

To install from `PyPi `_:

::

    pip install nbtransom

To install from this Git repo:

::

    git clone https://github.com/ceteri/nbtransom.git

    cd nbtransom

    pip install -r requirements.txt

Kudos

-----

`@htmartin `_

`@esztiorm `_

`@fperez `_

`@odewahn `_