{"id":25968845,"url":"https://github.com/daniel-keogh/emerging-tech-project","last_synced_at":"2026-04-11T12:03:09.904Z","repository":{"id":121011508,"uuid":"305179567","full_name":"daniel-keogh/emerging-tech-project","owner":"daniel-keogh","description":"A web service that uses machine learning to predict wind turbine power output from wind speed values defined in a given data set","archived":false,"fork":false,"pushed_at":"2021-01-03T11:45:59.000Z","size":1671,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-03-04T22:37:12.625Z","etag":null,"topics":["docker","flask","flask-application","jupyter-notebook","keras","machine-learning","machinelearning","python","python3","regression","regression-models","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Emerging Technologies Project\n\nY4S1 Emerging Technologies Project\n\n## Description\n\nA web service that uses machine learning to predict wind turbine power output from wind speed values defined in the data set [powerproduction.csv](./powerproduction.csv).\n\n## Running the Notebook\n\nThe model is created in a Jupyter notebook using Keras, and you can run the notebook by first installing [Anaconda](https://www.anaconda.com/) and then executing the below command from within the repository's root directory.\n\n```sh\n$ jupyter notebook\n```\n\n## Running the Web Service\n\nThe web service consists of a Flask application which serves a simple Vue.js frontend.\n\n![Frontend](https://user-images.githubusercontent.com/37158241/103477689-1ca81c80-4db9-11eb-9ce2-f7a691c8165e.png)\n\n### Development Server\n\nFirst run the following to install the necessary dependencies.\n\n```sh\n$ pip install -r requirements.txt\n```\n\nTo start a development server run the following command and then open `localhost:5000` in a web browser.\n\n```sh\n$ python app.py\n```\n\n### Docker\n\nYou can run the web service in a Docker container by following the steps below.\n\n#### Build Image\n\n```sh\n$ docker build -t power-production .\n```\n\n#### Run Image\n\n```sh\n$ docker run -d -p 5000:5000 power-production\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaniel-keogh%2Femerging-tech-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdaniel-keogh%2Femerging-tech-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaniel-keogh%2Femerging-tech-project/lists"}