{"id":20306458,"url":"https://github.com/drkbluescience/ibm-datascience-spacex","last_synced_at":"2026-05-10T17:52:03.036Z","repository":{"id":243245595,"uuid":"811375865","full_name":"drkbluescience/IBM-DataScience-SpaceX","owner":"drkbluescience","description":"In this project, we predict whether the Falcon 9 first stage will land successfully by following the data science methodology.","archived":false,"fork":false,"pushed_at":"2024-06-07T14:59:44.000Z","size":572,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-14T11:33:13.589Z","etag":null,"topics":["data-visualization","data-wrangling","machine-learning-algorithms","sql-query","sqlite","webscraping-data"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/drkbluescience.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":"2024-06-06T13:28:59.000Z","updated_at":"2024-06-07T15:05:15.000Z","dependencies_parsed_at":"2024-06-07T15:42:33.236Z","dependency_job_id":"3908ff09-c0ae-44b4-b4be-408a2348691c","html_url":"https://github.com/drkbluescience/IBM-DataScience-SpaceX","commit_stats":null,"previous_names":["drkbluescience/ibm-datascience-spacex"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/drkbluescience%2FIBM-DataScience-SpaceX","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/drkbluescience%2FIBM-DataScience-SpaceX/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/drkbluescience%2FIBM-DataScience-SpaceX/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/drkbluescience%2FIBM-DataScience-SpaceX/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/drkbluescience","download_url":"https://codeload.github.com/drkbluescience/IBM-DataScience-SpaceX/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241803055,"owners_count":20022766,"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":["data-visualization","data-wrangling","machine-learning-algorithms","sql-query","sqlite","webscraping-data"],"created_at":"2024-11-14T17:13:27.130Z","updated_at":"2026-05-10T17:52:02.997Z","avatar_url":"https://github.com/drkbluescience.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# SpaceX Falcon 9 first stage Landing Prediction\n\nIn this capstone project-[IBM-Applied Data Science Capstone](https://www.coursera.org/learn/applied-data-science-capstone), the successful landing of the Falcon 9 first stage is predicted. Data on Falcon 9 first-stage landings is collected using a RESTful API and web scraping. \nThe collected data is converted into a dataframe and then subjected to data wrangling.\n\nAn interactive dashboard is built using Plotly Dash to analyze the launch records. Additionally, an interactive map is created with Folium to examine the proximity of the launch sites. \nGoogle Colab was used for all notebooks except for interactive visual analytics and the dashboard, which were done in the local environment. The required Python packages for the environment are listed in the requirements.txt file.\n\nMachine learning is used to determine if the first stage of Falcon 9 will land successfully. The data is split into training and test sets to find the optimal hyperparameters for SVM, classification trees, and logistic regression. The best-performing method is then identified using the test data.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdrkbluescience%2Fibm-datascience-spacex","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdrkbluescience%2Fibm-datascience-spacex","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdrkbluescience%2Fibm-datascience-spacex/lists"}