{"id":18648478,"url":"https://github.com/minhaskamal/intellectron","last_synced_at":"2025-06-21T09:36:51.279Z","repository":{"id":72584152,"uuid":"58312747","full_name":"MinhasKamal/Intellectron","owner":"MinhasKamal","description":"An Infant Library of Artificial Neural Network (multilayer-deep-convolutional-machine-learning)","archived":false,"fork":false,"pushed_at":"2017-08-29T02:48:39.000Z","size":233,"stargazers_count":7,"open_issues_count":0,"forks_count":6,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-04-11T18:53:05.341Z","etag":null,"topics":["artificial-neural-networks","deep-learning","deep-learning-library","java","library","machine-learning","machine-learning-library","neural-network"],"latest_commit_sha":null,"homepage":"http://minhaskamal.github.io/Intellectron","language":"Java","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/MinhasKamal.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-05-08T13:14:38.000Z","updated_at":"2023-05-03T20:01:16.000Z","dependencies_parsed_at":null,"dependency_job_id":"09abb765-18e7-4df3-b0f9-a961acd737ad","html_url":"https://github.com/MinhasKamal/Intellectron","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/MinhasKamal/Intellectron","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MinhasKamal%2FIntellectron","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MinhasKamal%2FIntellectron/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MinhasKamal%2FIntellectron/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MinhasKamal%2FIntellectron/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MinhasKamal","download_url":"https://codeload.github.com/MinhasKamal/Intellectron/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MinhasKamal%2FIntellectron/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261101123,"owners_count":23109856,"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":["artificial-neural-networks","deep-learning","deep-learning-library","java","library","machine-learning","machine-learning-library","neural-network"],"created_at":"2024-11-07T06:31:15.043Z","updated_at":"2025-06-21T09:36:46.270Z","avatar_url":"https://github.com/MinhasKamal.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1\u003e\u003cimg src=\"https://user-images.githubusercontent.com/5456665/27328057-84566234-55d2-11e7-88ca-e4966a309633.png\" height=24px width=auto/\u003e Intellectron\u003c/h1\u003e\n\n#### An Infant Library of Artificial Neural Network\n\nThe project is a simple implementation of Deep Neural Network. Several machine learning algorithms are put together here. This tiny library is particularly suitable for small projects.\n\n### How to Use?\n1. Download [Intellectron.jar](https://github.com/MinhasKamal/Intellectron/releases/download/release/Intellectron-V0.1.jar), and [integrate](https://stackoverflow.com/a/3280451/4684058) it in your project's build path.\n2. Now, use it in your project like this-\n\n```\n\t// This is a demonstration of XOR gate implementation in Neural Network.\n\tpublic static void main(String[] args) {\n\t\t// For XOR gate-\n\t\t// ------------------\n\t\t// | input | output |\n\t\t// |----------------|\n\t\t// | 0 | 0 |   0    |\n\t\t// | 0 | 1 |   1    |\n\t\t// | 1 | 0 |   1    |\n\t\t// | 1 | 1 |   0    |\n\t\t// ------------------\n\t\tdouble[][] inputs = new double[][]{\n\t\t\t{0, 0}, {0, 1}, {1, 0}, {1, 1}\n\t\t};\n\t\tdouble[][] expectedOutputs = new double[][]{\n\t\t\t{0}, {1}, {1}, {0}\n\t\t};\n\t\t\n\t\t// Here, we are creating four layers of neural network.\n\t\t// First layer is created automatically using the input data.\n\t\t// Here the input has two categories, so first layer (input layer)\n\t\t// will have 2 neurons. \n\t\t// The second layer will contain- 4, third layer- 2, and fourth layer\n\t\t// (output layer) contains 1 neuron.\n\t\tint[] numbersOfNeuronsInLayers = new int[]{4, 2, 1};\n\t\t\n\t\t// The 'DeepNeuralNetworkImplementation' object takes the network \n\t\t// structure, learning rate, and number of inputs (input categories).\n\t\tDeepNeuralNetworkImplementation deepNeuralNetworkImplementation = \n\t\t\tnew DeepNeuralNetworkImplementation(numbersOfNeuronsInLayers, 0.1, 2);\n\t\t\n\t\t// Here we are running 20,000 cycles to train the network.\n\t\t// In each cycle we are passing the input and expected output.\n\t\tSystem.out.println(\"# Training...\\n\");\n\t\tint cycle = 20000;\n\t\tfor(int i=0; i\u003ccycle; i++){\n\t\t\tdeepNeuralNetworkImplementation.train(inputs, expectedOutputs);\n\t\t}\n\t\t\n\t\t// Storing knowledge in the memory storage\n\t\tSystem.out.println(\"# Storing Knowledge...\\n\");\n\t\tString workspace = System.getenv(\"SystemDrive\") + System.getenv(\"HOMEPATH\") + \"\\\\Desktop\\\\\";\n\t\tdeepNeuralNetworkImplementation.dump(workspace+\"knowledge.xml\");\n\t\t\n\t\t// Predicting output for inputs from acquired knowledge\n\t\tSystem.out.println(\"# Predicting...\");\n\t\tdouble prediction;\n\t\tprediction = deepNeuralNetworkImplementation.predict(new double[]{0, 0})[0];\n\t\tSystem.out.println(\"input- 0, 0; prediction- \"+prediction);\n\t\tprediction = deepNeuralNetworkImplementation.predict(new double[]{0, 1})[0];\n\t\tSystem.out.println(\"input- 0, 1; prediction- \"+prediction);\n\t\tprediction = deepNeuralNetworkImplementation.predict(new double[]{1, 0})[0];\n\t\tSystem.out.println(\"input- 1, 0; prediction- \"+prediction);\n\t\tprediction = deepNeuralNetworkImplementation.predict(new double[]{1, 1})[0];\n\t\tSystem.out.println(\"input- 1, 1; prediction- \"+prediction);\n\t}\n```\n\nYou can find some simple implementations in the [test](https://github.com/MinhasKamal/Intellectron/tree/master/src/test) section. There is also a beautiful project created with Intellectron- [DeepGenderRecognizer](https://github.com/MinhasKamal/DeepGenderRecognizer); you will get a nice insight from it too.\n\n### Releases\n- [Intellectron-V0.1.jar](https://github.com/MinhasKamal/Intellectron/releases/download/release/Intellectron-V0.1.jar)\n\n### License\n\n\u003ca rel=\"license\" href=\"https://opensource.org/licenses/MIT\"\u003e\u003cimg alt=\"MIT License\" src=\"https://cloud.githubusercontent.com/assets/5456665/18950087/fbe0681a-865f-11e6-9552-e59d038d5913.png\" width=\"60em\" height=auto/\u003e\u003c/a\u003e\u003cbr/\u003e\n\n\u003ca href=\"https://github.com/MinhasKamal/Intellectron\"\u003eIntellectron\u003c/a\u003e is licensed under \u003ca rel=\"license\" href=\"https://opensource.org/licenses/MIT\"\u003eMIT License\u003c/a\u003e.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fminhaskamal%2Fintellectron","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fminhaskamal%2Fintellectron","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fminhaskamal%2Fintellectron/lists"}