{"id":28075374,"url":"https://github.com/sevenjunebaby/aimodels","last_synced_at":"2025-05-13T00:56:43.367Z","repository":{"id":292898351,"uuid":"982308497","full_name":"sevenjunebaby/AiModels","owner":"sevenjunebaby","description":"Artificial intelligence models apply different algorithms to relevant data inputs to achieve the tasks, or output, they’ve been programmed for.","archived":false,"fork":false,"pushed_at":"2025-05-12T18:02:59.000Z","size":5,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-13T00:56:37.903Z","etag":null,"topics":["llm","python3","sckiit-learn"],"latest_commit_sha":null,"homepage":"https://scikit-learn.org/stable/auto_examples/model_selection/index.html","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sevenjunebaby.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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,"zenodo":null}},"created_at":"2025-05-12T17:26:18.000Z","updated_at":"2025-05-12T18:40:12.000Z","dependencies_parsed_at":"2025-05-12T18:39:32.807Z","dependency_job_id":"291e8aa5-f810-425a-8e4d-c47464195784","html_url":"https://github.com/sevenjunebaby/AiModels","commit_stats":null,"previous_names":["sevenjunebaby/aimodels"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sevenjunebaby%2FAiModels","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sevenjunebaby%2FAiModels/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sevenjunebaby%2FAiModels/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sevenjunebaby%2FAiModels/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sevenjunebaby","download_url":"https://codeload.github.com/sevenjunebaby/AiModels/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253850884,"owners_count":21973672,"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":["llm","python3","sckiit-learn"],"created_at":"2025-05-13T00:56:42.760Z","updated_at":"2025-05-13T00:56:43.352Z","avatar_url":"https://github.com/sevenjunebaby.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# AI model?\n\nAn AI model is a program that has been trained on a set of data to recognize certain patterns or make certain decisions without further human intervention. Artificial intelligence models apply different algorithms to relevant data inputs to achieve the tasks, or output, they’ve been programmed for.\n\nSimply put, an AI model is defined by its ability to autonomously make decisions or predictions, rather than simulate human intelligence. Among the first successful AI models were checkers- and chess-playing programs in the early 1950s: the models enabled the programs to make moves in direct response to the human opponent, rather than follow a pre-scripted series of moves.\n\nDifferent types of AI models are better suited for specific tasks, or domains, for which their particular decision-making logic is most useful or relevant. Complex systems often employ multiple models simultaneously, using ensemble learning techniques like bagging, boosting or stacking.\n\nAs AI tools grow increasingly complex and versatile, they require increasingly challenging amounts of data and computing power to train and execute. In response, systems designed to execute specific tasks in a single domain are giving way to foundation models, pre-trained on large, unlabeled datasets and capable of a wide array of applications. These versatile foundation models can then be fine-tuned for specific tasks.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsevenjunebaby%2Faimodels","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsevenjunebaby%2Faimodels","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsevenjunebaby%2Faimodels/lists"}