{"id":18510392,"url":"https://github.com/rakibhhridoy/webappclassifierstreamlit-python","last_synced_at":"2026-05-01T19:32:21.456Z","repository":{"id":131513692,"uuid":"287465717","full_name":"rakibhhridoy/WebAppClassifierStreamlit-Python","owner":"rakibhhridoy","description":"Machine Learning Training and Testing in Web App. It provide good learning interface for experimenting with different hyper parameter tuning and compare different algorithms with each other without writing code repeatedly.","archived":false,"fork":false,"pushed_at":"2020-08-14T11:26:15.000Z","size":279,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-17T02:41:54.985Z","etag":null,"topics":["classification","hyperparameter-optimization","hyperparameter-tuning","logistic-regression","machine-learning","python","random-forest","streamlit","support-vector-machines","svm-classifier","webapp"],"latest_commit_sha":null,"homepage":"https://rakibhhridoy.gihub.io","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/rakibhhridoy.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":"2020-08-14T06:56:48.000Z","updated_at":"2022-10-31T12:45:47.000Z","dependencies_parsed_at":"2023-03-17T13:00:38.457Z","dependency_job_id":null,"html_url":"https://github.com/rakibhhridoy/WebAppClassifierStreamlit-Python","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rakibhhridoy%2FWebAppClassifierStreamlit-Python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rakibhhridoy%2FWebAppClassifierStreamlit-Python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rakibhhridoy%2FWebAppClassifierStreamlit-Python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rakibhhridoy%2FWebAppClassifierStreamlit-Python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rakibhhridoy","download_url":"https://codeload.github.com/rakibhhridoy/WebAppClassifierStreamlit-Python/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254129552,"owners_count":22019629,"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":["classification","hyperparameter-optimization","hyperparameter-tuning","logistic-regression","machine-learning","python","random-forest","streamlit","support-vector-machines","svm-classifier","webapp"],"created_at":"2024-11-06T15:23:09.966Z","updated_at":"2026-05-01T19:32:16.429Z","avatar_url":"https://github.com/rakibhhridoy.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# *Web App Classifiers Streamlit \u0026 Python* \n![Web App](images/i0.png)\n\n### Available Machine learning Algorithms\n- [x] Support Vector Machine\n- [x] Logistic Regression\n- [x] Random Forest Classifier \n- [ ] KNN -On task\n- [ ] Decision Tree -On task\n- [ ] Naive Bayes -On task\n\n### Available Metrics\n- [x] Confusion Matrix\n- [x] Accuracy\n- [x] Precision\n- [x] Recall\n- [x] AUC ROC\n- [x] ROC Curve\n- [x] Precision Recall Curve\n- [ ] Validation Curve -On task\n- [ ] Learning Curve -On task\n\n### Set up guide\n\u003e First Get the repository files Downloading or Clonning the repository\n\u003e Now open the folder using any ide or editor and select python. Now navigate to console and type\n```bash\nstreamlit run app.py\n```\n\u003e It will open in localhost server. Now you can use it easily.\n\n### Customize Heading and Title of your Task\n```python\ndef main():\n    st.title('Binary Classification Web App')\n    st.sidebar.title('Binary Classifier App')\n    st.markdown(\"Are Your Mashroom poisonous?\")\n    st.sidebar.markdown(\"Are Your Mashroom poisonous?\")\n\n    @st.cache(persist = True)\n    def load_data():\n        df = pd.read_csv('data/mushrooms.csv')\n        le = LabelEncoder()\n\n        for col in df.columns:\n            df[col] = le.fit_transform(df[col])\n\n        return df\n```\nChange the title,sidebar title,markdown and sidebar markdown according to your project.\n\n### Environment \nMake sure you have all necessery python library installed. For this projects you need \n* Numpy\n* Pandas\n* Streamlit\n* Scikit-learn\n  \nif you don't have these libraries go to python or anaconda prompt and paste these:\n```bash\npip install numpy\npip install pandas\npip install streamlit\npip install sklearn\n```\n\n\n\n### Get touch with Me\nConnect- [Linkedin](https://linkedin.com/in/rakibhhridoy) \u003cbr\u003e\nWebsite- [RakibHHridoy](https://rakibhhridoy.github.io)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frakibhhridoy%2Fwebappclassifierstreamlit-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frakibhhridoy%2Fwebappclassifierstreamlit-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frakibhhridoy%2Fwebappclassifierstreamlit-python/lists"}