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https://github.com/athari22/applied-data-science-capstone
Applied-Data-Science-Capstone
https://github.com/athari22/applied-data-science-capstone
api classification data-analysis data-cleaning data-collection data-science data-scraping data-visualization data-wrangling knn machine-learning sql
Last synced: about 6 hours ago
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Applied-Data-Science-Capstone
- Host: GitHub
- URL: https://github.com/athari22/applied-data-science-capstone
- Owner: Athari22
- Created: 2022-10-03T12:41:48.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2022-10-03T16:05:05.000Z (about 2 years ago)
- Last Synced: 2023-12-10T10:25:21.239Z (11 months ago)
- Topics: api, classification, data-analysis, data-cleaning, data-collection, data-science, data-scraping, data-visualization, data-wrangling, knn, machine-learning, sql
- Language: Jupyter Notebook
- Homepage:
- Size: 3.03 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Applied Data Science Capstone
## Project Overview
This project is a part of the [IBM Data Science Professional Certificate](https://www.coursera.org/professional-certificates/ibm-data-science).
## Description
In this capstone, we will predict if the Falcon 9 first stage will land successfully. SpaceX advertises Falcon 9 rocket launches on its website, with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because SpaceX can reuse the first stage. Therefore if we can determine if the first stage will land, we can determine the cost of a launch. This information can be used if an alternate company wants to bid against SpaceX for a rocket launch. In this module, you will be provided with an overview of the problem and the tools you need to complete the course.
## Problems you want to find answers
- Determined the price of each launch.
- Predict if the Falcon 9 first stage will land successfully.
## Objective
- Writing Python code to manipulate data in a Pandas data frame.
- Conversion of a JSON file into a Create a Python Pandas data frame by converting a JSON file.
- Using data science methodologies to define and formulate a real-world business problem.
- Using your data analysis tools to load a dataset, clean it, and find out interesting insights from it.
## Methodology
1. [Data collection.](https://github.com/Athari22/Applied-Data-Science-Capstone/blob/main/Data-collection-api.ipynb)
2. [Data wrangling.](https://github.com/Athari22/Applied-Data-Science-Capstone/blob/main/Data%20wrangling.ipynb)
3. [Exploratory data analysis.](https://github.com/Athari22/Applied-Data-Science-Capstone/blob/main/eda-sql.ipynb)
4. [Data visualization.](https://github.com/Athari22/Applied-Data-Science-Capstone/blob/main/EDA%20with%20Visualization.ipynb)
5. [Model development.](https://github.com/Athari22/Applied-Data-Science-Capstone/blob/main/Machine_Learning_Prediction.ipynb)
6. [Model evaluation.](https://github.com/Athari22/Applied-Data-Science-Capstone/blob/main/Machine_Learning_Prediction.ipynb)
7. [Reporting.](https://github.com/Athari22/Applied-Data-Science-Capstone/blob/main/Data%20Science%20Capstone.pdf)
