{"id":17739028,"url":"https://github.com/pierrekieffer/neuralnetworkgenerator","last_synced_at":"2026-04-30T03:35:20.657Z","repository":{"id":120128923,"uuid":"160094784","full_name":"PierreKieffer/NeuralNetworkGenerator","owner":"PierreKieffer","description":"Test and generate the best Neural Net model based on a series of parameters ","archived":false,"fork":false,"pushed_at":"2019-06-21T09:17:34.000Z","size":7,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-06-26T03:37:06.118Z","etag":null,"topics":["deep-learning","keras","neural-networks"],"latest_commit_sha":null,"homepage":"","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/PierreKieffer.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}},"created_at":"2018-12-02T21:04:14.000Z","updated_at":"2020-05-02T10:56:52.000Z","dependencies_parsed_at":"2024-06-12T01:18:43.690Z","dependency_job_id":null,"html_url":"https://github.com/PierreKieffer/NeuralNetworkGenerator","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/PierreKieffer/NeuralNetworkGenerator","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PierreKieffer%2FNeuralNetworkGenerator","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PierreKieffer%2FNeuralNetworkGenerator/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PierreKieffer%2FNeuralNetworkGenerator/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PierreKieffer%2FNeuralNetworkGenerator/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/PierreKieffer","download_url":"https://codeload.github.com/PierreKieffer/NeuralNetworkGenerator/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PierreKieffer%2FNeuralNetworkGenerator/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32454095,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-29T22:27:22.272Z","status":"online","status_checked_at":"2026-04-30T02:00:05.929Z","response_time":57,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["deep-learning","keras","neural-networks"],"created_at":"2024-10-26T02:06:59.667Z","updated_at":"2026-04-30T03:35:20.641Z","avatar_url":"https://github.com/PierreKieffer.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# NeuralNetworkGenerator\nThis library provides full process to Test and generate the best Neural Net model based on a series of parameters \nfor a generic input dataframe \n\n### load_processed_data\n- load data  \n### generate_nn_list\n- Return a list of dictionnaries. Each dict has different param for a neural net. The input is a dict of parameters : \n\tparam_choices = {\n\t'nb_neurons' : [32,64,128],\n\t'nb_layers' : [3,4,5,6],\n\t'activation' : ['relu','elu','sigmoid'],\n\t'optimizer' : ['adam','rmsprop','adamax','sgd'],\n\t}\n### compile_model\n- Build a neural net from generate_nn_list output\n### train_networks\n- Classic Train and test models\n### cross_validation\n- Train and Test models on n differents train_test_split of the data, and return the score mean for each architecture of neural net\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpierrekieffer%2Fneuralnetworkgenerator","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpierrekieffer%2Fneuralnetworkgenerator","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpierrekieffer%2Fneuralnetworkgenerator/lists"}