{"id":19279670,"url":"https://github.com/freebirdscrew/datascience_crash_course","last_synced_at":"2026-04-29T23:04:26.524Z","repository":{"id":105992699,"uuid":"289004599","full_name":"FreeBirdsCrew/DataScience_Crash_Course","owner":"FreeBirdsCrew","description":"Data Science Crash Course that Explained about Each and Every Process in Data Science.","archived":false,"fork":false,"pushed_at":"2020-08-20T12:55:57.000Z","size":651,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-05T16:30:16.414Z","etag":null,"topics":["dash","data","datascience","datascience-crash-course","datascience-machinelearning","datascientist","datasets","freebirdscrew","matplotlib","numpy","numpy-library","pandas","plotly","plotly-python","python","python3","simranjeet","simranjeetsingh"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/FreeBirdsCrew.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2020-08-20T12:47:53.000Z","updated_at":"2024-11-12T05:46:23.000Z","dependencies_parsed_at":null,"dependency_job_id":"bb06b4c4-59df-42e3-9bf6-3a5ac88104e8","html_url":"https://github.com/FreeBirdsCrew/DataScience_Crash_Course","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/FreeBirdsCrew%2FDataScience_Crash_Course","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/FreeBirdsCrew%2FDataScience_Crash_Course/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/FreeBirdsCrew%2FDataScience_Crash_Course/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/FreeBirdsCrew%2FDataScience_Crash_Course/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/FreeBirdsCrew","download_url":"https://codeload.github.com/FreeBirdsCrew/DataScience_Crash_Course/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240385199,"owners_count":19792980,"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":["dash","data","datascience","datascience-crash-course","datascience-machinelearning","datascientist","datasets","freebirdscrew","matplotlib","numpy","numpy-library","pandas","plotly","plotly-python","python","python3","simranjeet","simranjeetsingh"],"created_at":"2024-11-09T21:15:59.710Z","updated_at":"2026-04-29T23:04:26.477Z","avatar_url":"https://github.com/FreeBirdsCrew.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DataScience_Crash_Course\n![screenshot](DataScience.png)\n\n## 🔴 Data Science Crash Course 🔴\n\n### YouTube Link - http://bit.ly/319NWmz\n\n💡It Contains Data Science from Scratch Tutorial, Explained Each and Every Step of Data Science Cycle or Processes.\nIn this Video, We Explained - \n\n1. Data Science \n2. Business Understanding\n3. Analytic Approach\n4. Data Mining or Extraction of Data\n5. Data Cleaning\n6. Data Exploration\n7. Feature Engineering\n8. Predictive Modeling\n9. Data Visualization\n10. Machine Learning Model on a Data Set that Compares all Machine Learning Models on their Accuracy and Precision.\n\n### 🔴 Algorithms that are in Comparision are - LogisticRegression, LinearDiscriminantAnalysis, KNeighborsClassifier, DecisionTreeClassifier, GaussianNB, SVC (Super Vector Machines).\nExplained about Data Visualization that tells about Plotly and Dash.\n\nTo get the Source Code, Follow me on \n### Github - https://bit.ly/3gg07Uc\n\nFollow us on Instagram and Telegram to get Updates on Projects and Ideas that We are Working On !!\n### Instagram - https://bit.ly/3jLR8vY\n### Telegram - https://bit.ly/30bstcE\n\n## 🔴Next Project - Series of Data Structure from Scratch with Python.\nThe More You Analyze, the More You Get Insights from the Data.\n\u003cbr /\u003e\n\nConnect with us:\n\n[\u003cimg align=\"left\" alt=\"FreeBirds Crew | YouTube\" width=\"22px\" src=\"https://cdn.jsdelivr.net/npm/simple-icons@v3/icons/youtube.svg\" /\u003e](https://www.youtube.com/channel/UC4RZP6hNT5gMlWCm0NDzUWg?view_as=subscriber?sub_confirmation=1)\n[\u003cimg align=\"left\" alt=\"FreeBirds Crew | Twitter\" width=\"22px\" src=\"https://cdn.jsdelivr.net/npm/simple-icons@v3/icons/twitter.svg\" /\u003e](https://twitter.com/CrewFreebirds)\n[\u003cimg align=\"left\" alt=\"FreeBirds Crew | LinkedIn\" width=\"22px\" src=\"https://cdn.jsdelivr.net/npm/simple-icons@v3/icons/linkedin.svg\" /\u003e](https://www.linkedin.com/in/simranjeet-singh-ab8071153/)\n[\u003cimg align=\"left\" alt=\"FreeBirds Crew | Instagram\" width=\"22px\" src=\"https://cdn.jsdelivr.net/npm/simple-icons@v3/icons/instagram.svg\" /\u003e](https://www.instagram.com/freebirdscrew/)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffreebirdscrew%2Fdatascience_crash_course","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffreebirdscrew%2Fdatascience_crash_course","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffreebirdscrew%2Fdatascience_crash_course/lists"}