craft ai Jupyter Notebook starter kit
craft ai cognitive automation API leverages explainable Artificial Intelligence to 10x your knowledge workers productivity. craft ai is the first high level AI API enabling Automated Machine Learning at the individual level that generates explainable predictive models on the fly.
The end goal: give an insight of the best New York city areas to find clients as a taxi driver. Using craft ai to analyze the 2017 yellow taxi trip records, this simple application learns when each NYC areas needs taxis.
- Download or clone the sources from GitHub,
- Install Python v3.7 on your computer, alternatively install any version of Python and install pyenv,
- Install pipenv to properly manage dependencies,
- Install the dependencies including craft ai python client, by running
pipenv installin the cloned or downloaded repository, from a terminal.
- Create a project following the subsection 1 of this tutorial and copy the write token
- in this directory, fill a
.envfile setting the following variable:
CRAFT_TOKENallows you to authenticate your calls to the craft ai API :
The following command will allow the user to access three notebooks:
Benchmarks.ipynb. We recommend to start by running
pipenv run notebook
- The principal work is done in
Preprocessing.ipynbhas been written to generate the dataset
Benchmarks.ipynballows the user to have a insight the Craft AI's agents performances.
What do next ?
You can use this use case as a
craftai.pandas example, and start your own projects with the tools provided by the library.
About the dataset
The work is based on the dataset
yellow.csv located in the directory data/. (It is possible to regenerate this dataset by using the notebook
yellow.csv has been extracted from the data available on the NYC Taxi and Limousine Commission (LTC) webpage.
The craft ai user documentation can be found at https://beta.craft.ai/doc and technical questions can be sent by email at email@example.com.