{"id":19220276,"url":"https://github.com/kinoute/l-layers-xor-neural-network","last_synced_at":"2026-05-04T15:39:49.682Z","repository":{"id":146859801,"uuid":"192222072","full_name":"kinoute/l-layers-xor-neural-network","owner":"kinoute","description":"A L-Layers XOR Neural Network using only Python and Numpy that learns to predict the XOR logic gates.","archived":false,"fork":false,"pushed_at":"2019-06-24T13:35:17.000Z","size":21,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-01-04T19:42:58.142Z","etag":null,"topics":["arguments","deep-learning","neural-network","numpy","python","python3","script","xor","xor-neural-network"],"latest_commit_sha":null,"homepage":null,"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/kinoute.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":"2019-06-16T18:08:47.000Z","updated_at":"2020-04-02T18:50:25.000Z","dependencies_parsed_at":null,"dependency_job_id":"386b6201-cb34-4d99-af5a-bdb9da842eb9","html_url":"https://github.com/kinoute/l-layers-xor-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/kinoute%2Fl-layers-xor-neural-network","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kinoute%2Fl-layers-xor-neural-network/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kinoute%2Fl-layers-xor-neural-network/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kinoute%2Fl-layers-xor-neural-network/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/kinoute","download_url":"https://codeload.github.com/kinoute/l-layers-xor-neural-network/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240293310,"owners_count":19778477,"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":["arguments","deep-learning","neural-network","numpy","python","python3","script","xor","xor-neural-network"],"created_at":"2024-11-09T14:34:41.767Z","updated_at":"2025-11-14T15:11:00.649Z","avatar_url":"https://github.com/kinoute.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# L-Layers XOR Neural Network\n\nA L-Layers XOR Neural Network using only Python and Numpy that learns to predict the XOR logic gates.\n\n## Script\n\nThe script was initially made as a `.ipynb` jupyter file and later refactored as a class and a script where arguments can be passed to the neural network.\n\nThere are two files:\n\n* `nn.py`: the main script that uses our NeuralNetwork class stored in the other file ;\n* `nn_xor_class.py`: our NeuralNetwork class.\n\n## Arguments\n\nYou can change the behavior of the Neural Network by using arguments when running the script. For example, you can change the activation function of the hidden layers, the learning rate etc. Here are the arguments allowed when running `nn.py`. All arguments are optional.\n\n### Usage\n\n```\npython nn.py [-h] [-l LAYERS] [-u UNITS] [-s SIZE] [-i ITERATIONS] [-r LEARNING_RATE]\n                    [-a {sigmoid,tanH,relu,leakyRelu}]\n\n  -h, --help            show this help message and exit\n\n  -l LAYERS, --layers LAYERS\n                        Number of layers in your NN (including the output layer). Default: 4.\n\n  -u UNITS, --units UNITS\n                        Number of units in each hidden layer separated by a\n                        comma (including output layer). Default:\n                        4,2,1.\n\n  -s SIZE, --size SIZE  How many examples should be generated in our training\n                        set. Default: 1000.\n\n  -i ITERATIONS, --iterations ITERATIONS\n                        Choose the number of iterations we want. Default: 10000.\n\n  -r LEARNING_RATE, --learning-rate LEARNING_RATE\n                        Pick a Learning rate for your neural Network. Default: 1.5.\n\n  -a {sigmoid,tanH,relu,leakyRelu}, --activation {sigmoid,tanH,relu,leakyRelu}\n                        Activation function for your hidden layers. The output\n                        layer will always be a sigmoid. Default: \"tanH\".\n\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkinoute%2Fl-layers-xor-neural-network","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkinoute%2Fl-layers-xor-neural-network","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkinoute%2Fl-layers-xor-neural-network/lists"}