{"id":18024094,"url":"https://github.com/thomasnield/kotlin_simple_neural_network","last_synced_at":"2025-07-08T11:38:18.566Z","repository":{"id":148076049,"uuid":"130620224","full_name":"thomasnield/kotlin_simple_neural_network","owner":"thomasnield","description":"A simple neural network application built in Kotlin","archived":false,"fork":false,"pushed_at":"2019-05-30T14:27:33.000Z","size":5790,"stargazers_count":50,"open_issues_count":2,"forks_count":10,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-03-05T20:11:26.919Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Kotlin","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/thomasnield.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":"2018-04-23T00:38:07.000Z","updated_at":"2024-02-21T03:09:44.000Z","dependencies_parsed_at":"2023-05-19T02:00:37.266Z","dependency_job_id":null,"html_url":"https://github.com/thomasnield/kotlin_simple_neural_network","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/thomasnield%2Fkotlin_simple_neural_network","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thomasnield%2Fkotlin_simple_neural_network/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thomasnield%2Fkotlin_simple_neural_network/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thomasnield%2Fkotlin_simple_neural_network/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/thomasnield","download_url":"https://codeload.github.com/thomasnield/kotlin_simple_neural_network/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244999396,"owners_count":20544873,"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":[],"created_at":"2024-10-30T07:11:52.735Z","updated_at":"2025-03-27T00:30:50.103Z","avatar_url":"https://github.com/thomasnield.png","language":"Kotlin","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Kotlin Simple Neural Network\n\n**PLEASE NOTE: This project has been [forked and moved here](https://github.com/thomasnield/kotlin-machine-learning-demos/) to showcase machine learning algorithms beyond neural networks.**\n\nThis is a simple neural network application that will suggest a LIGHT or DARK font for a given background color.\n\nThe training/predicting user interface was built with [TornadoFX](https://github.com/edvin/tornadofx).\n\n## YouTube Walkthrough\n\n[![](https://img.youtube.com/vi/tAioWlhKA90/hqdefault.jpg)](https://www.youtube.com/watch?v=tAioWlhKA90)\n\n## Featured at KotlinConf 2018 in Amsterdam\n\n[![](https://img.youtube.com/vi/-zTqtEcnM7A/hqdefault.jpg)](https://youtu.be/-zTqtEcnM7A)\n\n## Details\n\nCurrently there are three implementations: \n\n1) [Simple RGB formula](https://stackoverflow.com/questions/1855884/determine-font-color-based-on-background-color#1855903) \n2) My feed-forward brute force implementation (no backpropagation)\n3) [ojAlgo! Neural Network](http://www.ojalgo.org/)\n4) [DeepLearning4J](https://deeplearning4j.org/)\n\nFor this simple toy example ojAlgo seems to perform the best, and is light and the simplest to implement. DL4J is definitely more heavyweight (with many dependencies) but is a more robust framework for larger, data-intensive deep learning problems in production. DL4J also has a nice [Kotlin MNIST example](https://github.com/deeplearning4j/dl4j-examples/tree/master/dl4j-examples/src/main/kotlin/org/deeplearning4j/examples/feedforward/mnist). \n\nNote also there is now a button to pre-train 1345 categorized colors. \n\nTariq Rashid's book [Build Your Own Neural Network](https://www.amazon.com/Make-Your-Own-Neural-Network/dp/1530826608/) is a tremendous resource, as well as [3Blue1Brown's Video](https://www.youtube.com/watch?v=aircAruvnKk\u0026list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi). [Grokking Deep Learning](https://www.manning.com/books/grokking-deep-learning) is probably the most thorough and useful resource when you are ready to deep-dive.\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthomasnield%2Fkotlin_simple_neural_network","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fthomasnield%2Fkotlin_simple_neural_network","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthomasnield%2Fkotlin_simple_neural_network/lists"}