{"id":13527952,"url":"https://github.com/Palashio/libra","last_synced_at":"2025-04-01T11:30:48.168Z","repository":{"id":39738837,"uuid":"254755757","full_name":"Palashio/libra","owner":"Palashio","description":"Ergonomic machine learning for everyone.","archived":false,"fork":false,"pushed_at":"2023-06-12T21:28:58.000Z","size":190634,"stargazers_count":1912,"open_issues_count":48,"forks_count":108,"subscribers_count":89,"default_branch":"master","last_synced_at":"2024-07-27T13:07:38.740Z","etag":null,"topics":["auto-ml","machine-learning","neural-networks"],"latest_commit_sha":null,"homepage":"http://libradocs.org/","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/Palashio.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":".github/FUNDING.yml","license":"LICENSE.txt","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null},"funding":{"github":null,"patreon":null,"open_collective":"libra","ko_fi":null,"tidelift":null,"community_bridge":null,"liberapay":null,"issuehunt":null,"otechie":null,"custom":null}},"created_at":"2020-04-10T23:25:55.000Z","updated_at":"2024-07-25T15:13:02.000Z","dependencies_parsed_at":"2023-01-22T09:45:31.713Z","dependency_job_id":"d848b17c-ec4f-42c0-9de1-22fecdf280e8","html_url":"https://github.com/Palashio/libra","commit_stats":{"total_commits":1047,"total_committers":35,"mean_commits":"29.914285714285715","dds":0.5912129894937919,"last_synced_commit":"4767c9d079d65ebf8afb162fc08f0c261d8e1c60"},"previous_names":["palashio/verve"],"tags_count":11,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Palashio%2Flibra","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Palashio%2Flibra/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Palashio%2Flibra/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Palashio%2Flibra/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Palashio","download_url":"https://codeload.github.com/Palashio/libra/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":213475562,"owners_count":15592726,"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":["auto-ml","machine-learning","neural-networks"],"created_at":"2024-08-01T06:02:07.987Z","updated_at":"2024-11-02T13:30:58.223Z","avatar_url":"https://github.com/Palashio.png","language":"Python","funding_links":["https://opencollective.com/libra"],"categories":["Python"],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n\u003cimg src=\"/tools/data/gh_images/logo.png\" alt=\"drawing\" width=\"100\"/\u003e\n       \n# Libra\n\n**An ergonomic machine learning library for non-technical users. Save time. Blaze through ML.**\n\n[![Build Status](https://travis-ci.org/Palashio/libra.svg?branch=master)](https://travis-ci.org/Palashio/libra)\n[![Downloads](https://pepy.tech/badge/libra)](https://pepy.tech/project/libra)\n[![Slack](https://img.shields.io/badge/slack-chat-green.svg?logo=slack)](https://join.slack.com/t/the-libra-team/shared_invite/zt-ek6bpd47-hdIxXlRAenKfy5JNWe8bgw)\n\n[![PyPi](https://img.shields.io/badge/pypi%20package-1.0.0-blue)](https://pypi.org/project/libra/)\n[![Release](https://img.shields.io/badge/Next%20Release-Sep%2012-green)](https://pypi.org/project/libra/)\n[![Website shields.io](https://img.shields.io/website-up-down-blue-red/http/shields.io.svg)](https://libradocs.github.io//)\n[![Issues](https://img.shields.io/github/issues/Palashio/libra)]()\n\n\u003c/div\u003e\n\nCheck out our newer machine learning tool [Nylon](https://github.com/Palashio/nylon)!\n\n## Installation\n\nInstall latest release version:\n\n```\npip install -U libra\n```\n\nInstall directory from github:\n\n```\ngit clone https://github.com/Palashio/libra.git\ncd libra\npip install .\n```\n\nAlternatively you can build and use the docker image locally with:\n\n```\ndocker build . -f docker/libra-normal/Dockerfile -t libra\ndocker run -v /path/to/my/data:/data -it --rm libra\n```\n\nOr if you have [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) installed.\n\n```\ndocker build . -f docker/libra-gpu/Dockerfile -t libra-gpu\ndocker run -v /path/to/my/data:/data --gpus all -it --rm libra-gpu\n```\n## Usage: the basics\n\nThe core functionality of libra works through the `client` object. A new client object should be created for every dataset that you want to produce results for. All information about the models that're built, the plots that are generated, and the metrics are created will be stored in the object.\n\nYou can then call different queries on that client object, and the dataset you passed to it will be used. \n\n```python\nfrom libra import client\n\nnewClient = client('path/to/dataset') \nnewClient.neural_network_query('please model the median number of households')\n```\nNow, calling \n```python\nnewClient.info()\n```\nwill return a dictionary of all the information that was generated: \n\n```python\ndict_keys(['id', 'model', 'num_classes', 'plots', 'target', 'preprocessor', \n          'interpreter', 'test_data', 'losses', 'accuracy'])\n```\n\nOther queries can also be called on the same object, and will be appended to the `models` dictionary.\n\n```python\nnewClient.svm_query('predict the proximity to the ocean')\nnewClient.model().keys()\n\ndict_keys(['regression_ANN', svm'])\n```\n\n## Tutorials\n\n - Full documentation can be found at [libradocs.org](https://libradocs.org/). \n - A list of resources can be found on our [awesome-libra](https://github.com/Palashio/awesome-libra) repository. \n\n---\n \n\n## Asking for help\nWelcome to the Libra community!\n\nIf you have any questions, feel free to:\n1. [read the docs](https://libradocs.org/).\n2. [Search through the issues](https://github.com/Palashio/libra/issues?q=is%3Aissue+is%3Aclosed).\n3. [Ask on stackoverflow](https://stackoverflow.com/questions/ask?guided=false) with the tag libra.\n4. [Join our slack](https://join.slack.com/t/the-libra-team/shared_invite/zt-ek6bpd47-hdIxXlRAenKfy5JNWe8bgw).\n\n\n\n## Demos\n\n\n![alt-text](/tools/data/gh_images/gif.gif)\n\n## Contact\n\nShoot me an email at [ps9cmk@virginia.edu](mailto:ps9cmk@virginia.edu) if you'd like to get in touch!\n\nFollow me on [twitter](https://twitter.com/_pshah) for updates and my insights about modern AI!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FPalashio%2Flibra","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FPalashio%2Flibra","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FPalashio%2Flibra/lists"}