{"id":20625334,"url":"https://github.com/dsgiitr/visualml","last_synced_at":"2025-04-15T15:08:12.722Z","repository":{"id":54607256,"uuid":"260471397","full_name":"dsgiitr/VisualML","owner":"dsgiitr","description":"Interactive Visual Machine Learning Demos.","archived":false,"fork":false,"pushed_at":"2023-03-10T08:08:41.000Z","size":73554,"stargazers_count":114,"open_issues_count":11,"forks_count":23,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-04-15T15:07:57.631Z","etag":null,"topics":["autoencoder","deep-learning","logistic-regression","machine-learning","mlp-classifier","pca","style-transfer","svm","tensorflow-js","vanishing-gradient","visualizations"],"latest_commit_sha":null,"homepage":"http://visualml.dsgiitr.in","language":"CSS","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dsgiitr.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-05-01T13:54:56.000Z","updated_at":"2024-08-19T11:54:13.000Z","dependencies_parsed_at":"2023-02-15T06:46:52.271Z","dependency_job_id":null,"html_url":"https://github.com/dsgiitr/VisualML","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/dsgiitr%2FVisualML","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dsgiitr%2FVisualML/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dsgiitr%2FVisualML/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dsgiitr%2FVisualML/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dsgiitr","download_url":"https://codeload.github.com/dsgiitr/VisualML/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249094932,"owners_count":21211837,"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":["autoencoder","deep-learning","logistic-regression","machine-learning","mlp-classifier","pca","style-transfer","svm","tensorflow-js","vanishing-gradient","visualizations"],"created_at":"2024-11-16T13:09:18.285Z","updated_at":"2025-04-15T15:08:12.696Z","avatar_url":"https://github.com/dsgiitr.png","language":"CSS","readme":"\n\u003cp align=\"center\"\u003e\n  \u003cimg width=35% src=\"/img/visualml.png\" /\u003e\n\u003c/p\u003e\n\n-----------------------------------------------------------------------------------------------------------\n# Visual Machine Learning\n\nVisual Machine Learning contains a set of Machine Learning and Deep Learning interactive visualisation demos for developing intuition. These demos are developed using [TensorFlow.js](https://js.tensorflow.org) and can be executed directly in your browser. This project is an extension of ML examples from [tfjs-examples](https://github.com/tensorflow/tfjs-examples). We implement new demos, as well as, add additional features into the ones that already existed in TFJS. \n\nSome examples may require web-gl enabled browsers and viewers may experience latency during executing the demos based on the device. \n\n# Overview of Demos\n\n\u003ctable\u003e\n  \u003ctr\u003e\n    \u003cth\u003eExample name\u003c/th\u003e\n    \u003cth\u003eDemo link\u003c/th\u003e\n    \u003cth\u003eInput data type\u003c/th\u003e\n    \u003cth\u003eTask type\u003c/th\u003e\n    \u003cth\u003eModel type\u003c/th\u003e\n    \u003cth\u003eTraining\u003c/th\u003e\n    \u003cth\u003eInference\u003c/th\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"./ANN\"\u003eANN\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://dsgiitr.github.io/ann-demo\"\u003e🔗\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003eIris Dataset\u003c/td\u003e\n    \u003ctd\u003eView NN architecture, View Confusion Matrix\u003c/td\u003e\n    \u003ctd\u003eMultilayer perceptron\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"./Autoencoder\"\u003eAutoencoder\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://dsgiitr.github.io/autoencoder-demo\"\u003e🔗\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003eMNIST dataset\u003c/td\u003e\n    \u003ctd\u003eVisualising Latent Space\u003c/td\u003e\n    \u003ctd\u003eAutoencoder\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"./Logistic Regression\"\u003eLogistic Regression\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://dsgiitr.github.io/logistic-regression-demo\"\u003e🔗\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003eVarious 2D data\u003c/td\u003e\n    \u003ctd\u003eVisualising Decision Boundary\u003c/td\u003e\n    \u003ctd\u003eLogistic Regression\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"./MNIST-CNN\"\u003eMNIST-CNN\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://dsgiitr.github.io/mnist-cnn-demo\"\u003e🔗\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003eMNIST\u003c/td\u003e\n    \u003ctd\u003eVisualising Activations\u003c/td\u003e\n    \u003ctd\u003eCNN\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"./PCA\"\u003ePCA\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://dsgiitr.github.io/pca-demo\"\u003e🔗\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003eVarious\u003c/td\u003e\n    \u003ctd\u003eVisualising Principal Components \u0026 projected dimensions\u003c/td\u003e\n    \u003ctd\u003ePCA\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"./SVM\"\u003eSVM\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://dsgiitr.github.io/svm-demo\"\u003e🔗\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e2D Dataset\u003c/td\u003e\n    \u003ctd\u003eVisualising Support Vectors and Kernels\u003c/td\u003e\n    \u003ctd\u003eSMO\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"./neural_style_transfer\"\u003eNeural Style Transfer\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://dsgiitr.github.io/neural-style-transfer-tfjs\"\u003e🔗\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003eImage Data\u003c/td\u003e\n    \u003ctd\u003eVisualising Style Transfer using MobileNet\u003c/td\u003e\n    \u003ctd\u003eStyle Transfer\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"./vanishing_gradients\"\u003eVanishing Gradients\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://dsgiitr.github.io/vanishing-gradients-demo\"\u003e🔗\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003eIris Dataset\u003c/td\u003e\n    \u003ctd\u003eDeveloping Intuition how Relu Fixes Vanishing Gradients\u003c/td\u003e\n    \u003ctd\u003eNeural Networks\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n    \u003ctd\u003eBrowser\u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/table\u003e\n\n# Dependencies\n\nAll the examples require the following dependencies to be installed.\n\n - Node.js version 8.9 or higher\n - [NPM CLI](https://docs.npmjs.com/cli/npm) OR [Yarn](https://yarnpkg.com/en/)\n\n## How to build?\n`cd` into the directory\n\nIf you are using `yarn`:\n\n```sh\ncd MNIST-CNN\nyarn\nyarn watch\n```\n\nIf you are using `npm`:\n```sh\ncd MNIST-CNN\nnpm install\nnpm run watch\n```\n\n### Details\n\nThe convention is that each example contains two scripts:\n\n- `yarn watch` or `npm run watch`: This starts and generates a local development HTML server tracking filesystem for changes, supporting hot-reloading.\n\n- `yarn build` or `npm run build`: generates a `dist/` folder which contains the build artifacts and can be used for deployment.\n\n## Contributing\n\nIf you want to contribute a demo, please reach out to us on\n[Github issues](https://github.com/dsgiitr/VisualML/issues)\nbefore sending us a pull request as we are trying to keep this set of examples\nsmall and highly curated.\n\n## Acknowledgements\n\n* [tfjs-examples](https://github.com/tensorflow/tfjs-examples)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdsgiitr%2Fvisualml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdsgiitr%2Fvisualml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdsgiitr%2Fvisualml/lists"}