{"id":19544346,"url":"https://github.com/chakki-works/karura","last_synced_at":"2025-04-26T17:32:56.793Z","repository":{"id":62573815,"uuid":"81906406","full_name":"chakki-works/karura","owner":"chakki-works","description":"karura enables you to use machine learning automatically \u0026 interactively","archived":false,"fork":false,"pushed_at":"2018-12-10T03:51:40.000Z","size":1094,"stargazers_count":72,"open_issues_count":0,"forks_count":5,"subscribers_count":13,"default_branch":"master","last_synced_at":"2025-04-04T17:02:26.678Z","etag":null,"topics":["kintone","machine-learning","slackbot"],"latest_commit_sha":null,"homepage":"https://youtu.be/moZOLXPjjAo","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/chakki-works.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-02-14T04:53:04.000Z","updated_at":"2024-04-29T19:45:48.000Z","dependencies_parsed_at":"2022-11-03T17:30:33.852Z","dependency_job_id":null,"html_url":"https://github.com/chakki-works/karura","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chakki-works%2Fkarura","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chakki-works%2Fkarura/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chakki-works%2Fkarura/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chakki-works%2Fkarura/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/chakki-works","download_url":"https://codeload.github.com/chakki-works/karura/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251026601,"owners_count":21525005,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["kintone","machine-learning","slackbot"],"created_at":"2024-11-11T03:27:50.401Z","updated_at":"2025-04-26T17:32:56.223Z","avatar_url":"https://github.com/chakki-works.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# karura\n\nkarura enables you to use machine learning automatically \u0026 interactively.\n\n![karura_concept](./doc/karura_concept.png)\n\n## Architecture\n\nkarura has insights. \n\nEach insight gets the data and judges the necessity of its adoption, and if it needed, execute it.\n\n![insight.png](./doc/insight.png)\n\nFor example, [`NAFrequencyCheckInsight`](https://github.com/chakki-works/karura/blob/master/karura/core/insights/na_frequency_insight.py) 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.\n\nkarura can have many insights, so you can add the insight as you needed. \n\n![stack_insights](./doc/stack_insights.png)\n\nInsights are adopted according to the [InsightIndex](https://github.com/chakki-works/karura/blob/master/karura/core/insight.py#L61) order.  \nAnd you can create custom insight by inheriting the [`Insight`](https://github.com/chakki-works/karura/blob/master/karura/core/insight.py) class.\n\n\n**karura is multi-language application. Now supports `ja` and `en`.**  \n(Some message on kintone is only Japanese).\n\n\n## Usage\n\n### In the Jupyter Notebook\n\nYou can use karura as your partner for data analytics.\n\n[karura notebook](https://github.com/chakki-works/karura/blob/master/doc/karura_notebook_demo.ipynb)\n\nTo install karura, pip install.\n\n```\npip install karura\n```\n\nThe dependencies as followings.\n\n* numpy\n* scipy\n* scikit-learn\n* matplotlib\n* pandas\n\nIf you use Slack integration, additionally install below.\n\n* slackbot\n\nIf you use kintone integration, additionally install below.\n\n* pykintone\n* tornado\n* cryptography\n* pymongo (Also needs MongoDB)\n\n\n### As Slackbot\n\nYou can communicate with karura on [Slack](https://slack.com/)!\n\n![karura_as_slackbot.PNG](./doc/karura_as_slackbot.PNG)\n\nWhen 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.\n\n\n### As Adviser on kintone\n\nYou can ask karura to analyze your kintone app!\n\n![karura_on_kintone.PNG](./doc/karura_on_kintone.PNG)\n\n* Select the target app\n* Select the field that you want to predict and fields that you use to do it\n* Push Train button\n\nThen, you can get analyzed result!\n\n## Setup\n\n### Slackbot\n\n* Use Dockerfile_slackbot\n* set below environmental variables\n  * SLACK_TOKEN: Your Slack token\n  * LANG: language that you want to use (`ja` or `en`)\n\n### kintone\n\n**[Tutorial is available (ja)](http://qiita.com/icoxfog417/private/ba6cc8c804f09fd2b16e)**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchakki-works%2Fkarura","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchakki-works%2Fkarura","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchakki-works%2Fkarura/lists"}