{"id":23878340,"url":"https://github.com/jacaranda-analytics/jacaranda","last_synced_at":"2026-05-09T16:07:01.540Z","repository":{"id":88711916,"uuid":"574484858","full_name":"jacaranda-analytics/jacaranda","owner":"jacaranda-analytics","description":"Jacaranda provides an easy interface to produce and tune AI and Machine learning models.","archived":false,"fork":false,"pushed_at":"2022-12-20T09:50:00.000Z","size":28,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-03T21:20:28.224Z","etag":null,"topics":["data-science","kaggle","machine-learning","neural-network","pytorch","xgboost"],"latest_commit_sha":null,"homepage":"https://pypi.org/project/jacaranda/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jacaranda-analytics.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-12-05T12:20:00.000Z","updated_at":"2022-12-07T09:41:18.000Z","dependencies_parsed_at":null,"dependency_job_id":"5842af65-bbaa-43b3-9ea3-3fe3a5b956f1","html_url":"https://github.com/jacaranda-analytics/jacaranda","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacaranda-analytics%2Fjacaranda","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacaranda-analytics%2Fjacaranda/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacaranda-analytics%2Fjacaranda/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacaranda-analytics%2Fjacaranda/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jacaranda-analytics","download_url":"https://codeload.github.com/jacaranda-analytics/jacaranda/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240245909,"owners_count":19771028,"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":["data-science","kaggle","machine-learning","neural-network","pytorch","xgboost"],"created_at":"2025-01-03T21:20:12.472Z","updated_at":"2025-10-13T17:37:38.215Z","avatar_url":"https://github.com/jacaranda-analytics.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"Jacaranda \n========================\n[![PyPI version](https://badge.fury.io/py/jacaranda.svg)](https://badge.fury.io/py/jacaranda) [![GitHub version](https://badge.fury.io/gh/jacaranda-analytics%2Fjacaranda.svg)](https://badge.fury.io/gh/jacaranda-analytics%2Fjacaranda)[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\n\n\u003c!-- markdown-toc start - Don't edit this section. Run M-x markdown-toc-refresh-toc --\u003e\n**Table of Contents**\n\n- [Jacaranda ](#jacaranda)\n- [Description](#description)\n- [Examples](#examples)\n- [Installation](#installation)\n    - [GitHub](#github)\n    - [Pip](#pip)\n- [Examples](#examples-1)\n- [License](#license)\n\n\u003c!-- markdown-toc end --\u003e\n\n\n# Description \n\nJacaranda is a wrapper package around several Data Science and Machine Learning\nlibrarys,  such as \n\n- [PyTorch](https://pytorch.org)\n- [XGboost](https://xgboost.readthedocs.io/en/stable/)\n\nwhich creates an easy interface to interact, and automatically tune models produced \nby these libraries. \n\n\n# Examples \n\nExamples for using the Jacaranda API to tune the following list of models is available in the examples folder. \n\n- Autoencoder \n- Variational Autoencode \n- Xgboost decicion tree\n- 1D Convolutional Neural Network \n- Multilayer Perceptron \n\n\n# Installation \n\nCurrently, there are various ways this package can be installed. \nThese include \n\n- GitHub \n- pip\n\n## GitHub \n\nTo install from GitHub there are two options, \nthe first option is to clone the repository and do a local installation from the cloned directory. \n\n```sh\ngit clone git@github.com:jacaranda-analytics/jacaranda.git\ncd jacaranda/ \u0026\u0026 pip install . \n```\n\nThe second option is to install from GitHub without first cloning the repository, \nto install the latest master branch, run the command. \n\n```sh\npip install https://github.com/jacaranda-analytics/jacaranda/archive/master.zip\n```\n\n## Pip \n\nTo install through pip, simply run \n\n```python \npip install jacaranda\n```\n\n\n\n# License \n\n- [MIT](LICENSE.md)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjacaranda-analytics%2Fjacaranda","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjacaranda-analytics%2Fjacaranda","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjacaranda-analytics%2Fjacaranda/lists"}