{"id":21156147,"url":"https://github.com/corvuscodex/kenoai","last_synced_at":"2025-10-28T23:50:25.127Z","repository":{"id":193679819,"uuid":"689294760","full_name":"CorvusCodex/KenoAi","owner":"CorvusCodex","description":"KenoAi is a keno prediction artificial intelligence that uses machine learning to predict numbers of next draw in kino 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align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/CorvusCodex/KenoAi/blob/main/KenoAi.png?raw=true\"\u003e\n\u003c/p\u003e\n\n# KenoAi\nKenoAi is a keno prediction artificial intelligence that uses machine learning to predict numbers of next draw in kino games.\n\n## For people without technical experience you can buy the compiled standalone application for windows from here:\nhttps://www.buymeacoffee.com/CorvusCodex/e/166132\n\n## Installation\n\nTo install KenoAi, you will need to have Python 3.x and the following libraries installed:\n- numpy\n- tensorflow\n- keras\n- art\n\nYou can install these libraries using pip by running the following command:\n\n'''pip install numpy tensorflow keras art'''\n\n## Usage\n\nTo use KenoAi, you will need to have a data (data.txt) file containing past keno results. This file should be in a comma-separated format, with each row representing a single draw and the numbers in descending order, rows are in new line without comma. Dont use white spaces. Last row number must have nothing after last number.\n\nOnce you have the data file, you can run the `KenoAi` script to train the model and generate predictions. The script will print the generated next draw with 20 numbers to the console.\n\n\u003eSupport my work:\u003cbr\u003e\n\u003eBTC: bc1q7wth254atug2p4v9j3krk9kauc0ehys2u8tgg3\u003cbr\u003e\n\u003eETH \u0026 BNB: 0x68B6D33Ad1A3e0aFaDA60d6ADf8594601BE492F0\u003cbr\u003e\n\u003eBuy me a coffee: https://www.buymeacoffee.com/CorvusCodex\n\n## Disclaimer\n\nThe code within this repository comes with no guarantee, the use of this code is your responsibility. I take NO responsibility and/or liability for how you choose to use any of the source code available here. By using any of the files available in this repository, you understand that you are AGREEING TO USE AT YOUR OWN RISK. Once again, ALL files available here are for EDUCATION and/or RESEARCH purposes ONLY.\nPlease keep in mind that while KenoAi.py uses advanced machine learning techniques to predict keno draw numbers, there is no guarantee that its predictions will be ever accurate. Keno results are inherently random and unpredictable, so it is important to use KenoAi responsibly and not rely on its predictions.\n\n\n## MIT License\n\nCopyright (c) 2025 CorvusCodex\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcorvuscodex%2Fkenoai","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcorvuscodex%2Fkenoai","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcorvuscodex%2Fkenoai/lists"}