karura enables you to use machine learning automatically & interactively.
karura has insights.
Each insight gets the data and judges the necessity of its adoption, and if it needed, execute it.
NAFrequencyCheckInsight watches the amount of the
NA in each column, and if it is too high, then drop the column. Of course, you can confirm it to the user.
karura can have many insights, so you can add the insight as you needed.
karura is multi-language application. Now supports
(Some message on kintone is only Japanese).
In the Jupyter Notebook
You can use karura as your partner for data analytics.
To install karura, pip install.
pip install karura
The dependencies as followings.
If you use Slack integration, additionally install below.
If you use kintone integration, additionally install below.
- pymongo (Also needs MongoDB)
You can communicate with karura on Slack!
When you upload the csv file or tell kintone app name to karura, then interaction starts.You can build your own machine learning model interactively, and also you can get some suggestions about the data treatment from karura.
As Adviser on kintone
You can ask karura to analyze your kintone app!
- Select the target app
- Select the field that you want to predict and fields that you use to do it
- Push Train button
Then, you can get analyzed result!
- Use Dockerfile_slackbot
- set below environmental variables
- SLACK_TOKEN: Your Slack token
- LANG: language that you want to use (