{"id":19555264,"url":"https://github.com/lugq1990/neural-nets","last_synced_at":"2026-05-17T14:33:30.646Z","repository":{"id":144093919,"uuid":"150697691","full_name":"lugq1990/neural-nets","owner":"lugq1990","description":"Build deep learning models more efficient based on TensorFlow.","archived":false,"fork":false,"pushed_at":"2018-09-28T07:00:50.000Z","size":121,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-02-26T07:41:45.415Z","etag":null,"topics":["deep-learning","deep-neural-networks","machine-learning","tensorflow"],"latest_commit_sha":null,"homepage":null,"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/lugq1990.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","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":"2018-09-28T06:48:50.000Z","updated_at":"2021-08-20T01:58:01.000Z","dependencies_parsed_at":null,"dependency_job_id":"ad345623-a68a-4644-b6b0-03b9d2a0ffa2","html_url":"https://github.com/lugq1990/neural-nets","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/lugq1990/neural-nets","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lugq1990%2Fneural-nets","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lugq1990%2Fneural-nets/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lugq1990%2Fneural-nets/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lugq1990%2Fneural-nets/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lugq1990","download_url":"https://codeload.github.com/lugq1990/neural-nets/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lugq1990%2Fneural-nets/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33142179,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-17T09:28:26.183Z","status":"ssl_error","status_checked_at":"2026-05-17T09:27:52.702Z","response_time":107,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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","deep-neural-networks","machine-learning","tensorflow"],"created_at":"2024-11-11T04:32:57.916Z","updated_at":"2026-05-17T14:33:28.505Z","avatar_url":"https://github.com/lugq1990.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# neural-nets\n\nBuild advanced deep learning models in one line. Most quickest and easiest way to build deep learning models.\n\n## Getting Started\n\nIn recent years, most popular technology in AI is Deep Learning. It has showed it power in many domains, such as image, natual language processing, voice and so on. If you want to use AI models for your goals to be solved better, use deep learning! If you find many machine learning predicted not well, use deep learning!\n\nSo deep learning can do lots of works, but how to use it? Thanks to Google teams, there is a great way to build models by using TensorFlow! This is based on TensorFlow to build many deep learning models, such as basic: # DNN, # RNN, # CNN, also with some advanced and more powerful model structure, such as: # ResidualNet, # DenseNet, # LSTM, # GRU and # Wide\u0026Deep. And in machine learning domain, there are two main categories to be solved: Classification(binary, multiclass) and regression. They are all supported, you only need to change one parameter to rebuild your models. Great.\n\n### Installing\n\nGit remote repository or clone source code to disk, in neuralNets directory:\n\n```\npython setup.py install\n```\n\n### OKay, show some examples how to use.\n\n```python\nfrom sklearn.datasets import load_iris\nfrom sklearn.model_selection import train_test_split\nfrom neuralNets.dnnNets import dnnNet\n\niris = load_iris()\nx, y = iris.data, iris.target\nxtrain, xtest, ytrain, ytest = train_test_split(x, y, test_size=.2)\n\nmodel = dnnNet(3, 4, n_layers=2, n_units=64, use_batch=False)\nmodel.fit(xtrain, ytrain, epochs=200)\ntest_acc = model.evaluate(xtest, ytest)\npred = model.predict(xtest)\nmodel.plot_acc()\n```\n![acc_curve](image/acc.png?raw=true)\n![loss_curve](image/loss.png?raw=true)\n\nEasy?\n\nAny problems are welcome!\n\n## Contributing\n\nAll contributions or issues are welcome!\n\n## Authors\n\n* **lugq** - *Initial work* - [lugq1990](https://github.com/lugq1990)\n\n### Paper links:\nLSTM:https://www.isca-speech.org/archive/archive_papers/interspeech_2012/i12_0194.pdf\nGRU:https://arxiv.org/pdf/1412.3555.pdf\nGoogleNet:https://www.cs.unc.edu/~wliu/papers/GoogLeNet.pdf\nResidualNet:https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/He_Deep_Residual_Learning_CVPR_2016_paper.pdf\n\n### Happy Deep Learning Modeling.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flugq1990%2Fneural-nets","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flugq1990%2Fneural-nets","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flugq1990%2Fneural-nets/lists"}