{"id":23975959,"url":"https://github.com/manuelseeger/rl-quadcopter-2","last_synced_at":"2026-05-11T07:41:05.984Z","repository":{"id":101804283,"uuid":"194542395","full_name":"manuelseeger/RL-Quadcopter-2","owner":"manuelseeger","description":"My implementation of Udacity ML Nanodegree Quadcopter project","archived":false,"fork":false,"pushed_at":"2019-06-30T17:30:28.000Z","size":9719,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-02-24T17:16:14.458Z","etag":null,"topics":["ddpg","deep-learning","deep-reinforcement-learning","keras","machine-learning","nanodegree","notebook","python","quadcopter","reinforcement-learning","sacred","udacity"],"latest_commit_sha":null,"homepage":null,"language":"HTML","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/manuelseeger.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,"zenodo":null}},"created_at":"2019-06-30T17:21:23.000Z","updated_at":"2024-06-19T16:21:43.000Z","dependencies_parsed_at":null,"dependency_job_id":"9731b1ab-1f3e-4a48-a805-31c90cd2d5ef","html_url":"https://github.com/manuelseeger/RL-Quadcopter-2","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/manuelseeger/RL-Quadcopter-2","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/manuelseeger%2FRL-Quadcopter-2","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/manuelseeger%2FRL-Quadcopter-2/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/manuelseeger%2FRL-Quadcopter-2/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/manuelseeger%2FRL-Quadcopter-2/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/manuelseeger","download_url":"https://codeload.github.com/manuelseeger/RL-Quadcopter-2/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/manuelseeger%2FRL-Quadcopter-2/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260865495,"owners_count":23074649,"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":["ddpg","deep-learning","deep-reinforcement-learning","keras","machine-learning","nanodegree","notebook","python","quadcopter","reinforcement-learning","sacred","udacity"],"created_at":"2025-01-07T06:55:00.073Z","updated_at":"2026-05-11T07:41:00.961Z","avatar_url":"https://github.com/manuelseeger.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Deep RL Quadcopter Controller\n\n*Teach a Quadcopter How to Fly!*\n\nIn this project, you will design an agent to fly a quadcopter, and then train it using a reinforcement learning algorithm of your choice! \n\n## Project Instructions\n\n1. Clone the repository and navigate to the downloaded folder.\n\n```\ngit clone https://github.com/udacity/RL-Quadcopter-2.git\ncd RL-Quadcopter-2\n```\n\n2. Create and activate a new environment.\n\n```\nconda create -n quadcop python=3.6 matplotlib numpy pandas keras sacred pymongo gym IPython\nsource activate quadcop\n```\n\n3. Create an [IPython kernel](http://ipython.readthedocs.io/en/stable/install/kernel_install.html) for the `quadcop` environment. \n```\npython -m ipykernel install --user --name quadcop --display-name \"quadcop\"\n```\n\n4. Open the notebook.\n```\njupyter notebook Quadcopter_Project.ipynb\n```\n\n5. Before running code, change the kernel to match the `quadcop` environment by using the drop-down menu (**Kernel \u003e Change kernel \u003e quadcop**). Then, follow the instructions in the notebook.\n\n6. You will likely need to install more pip packages to complete this project.  Please curate the list of packages needed to run your project in the `requirements.txt` file in the repository.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmanuelseeger%2Frl-quadcopter-2","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmanuelseeger%2Frl-quadcopter-2","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmanuelseeger%2Frl-quadcopter-2/lists"}