{"id":14958207,"url":"https://github.com/mg380/ibm-applied-data-science-capstone","last_synced_at":"2026-03-05T18:40:57.889Z","repository":{"id":253731871,"uuid":"844353344","full_name":"mg380/IBM-Applied-Data-Science-Capstone","owner":"mg380","description":"This Capstone is the 10th (final) course in IBM Data Science Professional Certificate specialization, and it actually summarises in the form of project all materials that have been learned during this specialization","archived":false,"fork":false,"pushed_at":"2024-08-23T04:42:20.000Z","size":6750,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-31T02:02:01.463Z","etag":null,"topics":["capstone","data","data-analysis","data-science","datascience","ibm","machine-learning","plotly","python","scikit-learn","sql"],"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/mg380.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":"2024-08-19T04:40:20.000Z","updated_at":"2024-08-23T04:43:49.000Z","dependencies_parsed_at":"2024-09-29T06:18:13.181Z","dependency_job_id":null,"html_url":"https://github.com/mg380/IBM-Applied-Data-Science-Capstone","commit_stats":{"total_commits":12,"total_committers":2,"mean_commits":6.0,"dds":0.08333333333333337,"last_synced_commit":"57c571570d5cec08c09e5e1bf14e6808fa14a7e5"},"previous_names":["mg380/ibm-applied-data-science-capstone"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mg380%2FIBM-Applied-Data-Science-Capstone","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mg380%2FIBM-Applied-Data-Science-Capstone/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mg380%2FIBM-Applied-Data-Science-Capstone/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mg380%2FIBM-Applied-Data-Science-Capstone/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mg380","download_url":"https://codeload.github.com/mg380/IBM-Applied-Data-Science-Capstone/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":237982289,"owners_count":19397236,"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":["capstone","data","data-analysis","data-science","datascience","ibm","machine-learning","plotly","python","scikit-learn","sql"],"created_at":"2024-09-24T13:16:28.508Z","updated_at":"2025-10-24T14:31:05.986Z","avatar_url":"https://github.com/mg380.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# IBM Applied Data Science Capstone\nThis Capstone is the professional certification project for [IBM Data Science Professional Certificate](https://www.coursera.org/professional-certificates/ibm-data-science) specialization, and summarizesthe project materials learned during this specialization.\n\n## Final Presentation\nPlease refer to the final presentation document for the overview of the task and results. The slides will guide the viewer through the different stages of the project and links are provided to the apporpriate coding tasks.\n\n[\u003cimg src=\"https://github.com/mg380/IBM-Applied-Data-Science-Capstone/blob/main/figs/presentation%20first%20page.png\" width=\"window.innerWidth\" height=\"auto\"\u003e](https://github.com/mg380/IBM-Applied-Data-Science-Capstone/blob/main/ds-capstone-template-coursera.pdf)\n\n\n\n## :page_facing_up: Project Background\nSpaceX is the most successful company of the commercial space \nage, making space travel affordable. The company advertises Falcon \n9 rocket launches on its website, with a cost of 62 million dollars; \nother providers cost upward of 165 million dollars each, much of the \nsavings is because SpaceX can reuse the first stage. Therefore, if we \ncan determine if the first stage will land, we can determine the cost \nof a launch. Based on public information and machine learning \nmodels, we are going to predict if SpaceX will reuse the first stage.\n## :page_facing_up: Questions to be answered \n- How do variables such as payload mass, launch site, number of \nflights, and orbits affect the success of the first stage landing? \n- Does the rate of successful landings increase over the years? \n- What is the best algorithm that can be used for binary classification \nin this case?\n## :page_facing_up: Methodology\n  ### 1. Data collection methodology\n  - Using SpaceX Rest API\n  - Using Web Scrapping from Wikipedia\n  ### 2. Performed data wrangling\n  - Filtering the data\n  - Dealing with missing values\n  - Using One Hot Encoding to prepare the data to a binary classification\n  ### 3. Performed exploratory data analysis (EDA) using visualization and SQL\n  ### 4. Performed interactive visual analytics using Folium and Plotly Dash\n  ### 5. Performed predictive analysis using classification models\n  - Building, tuning and evaluation of classification models to ensure the best\n  results\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmg380%2Fibm-applied-data-science-capstone","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmg380%2Fibm-applied-data-science-capstone","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmg380%2Fibm-applied-data-science-capstone/lists"}