https://github.com/vishal-038/datascience_capstone_project

SpaceX Falcon 9 First Stage Landing Prediction Our project focuses on predicting the success of Falcon 9 first-stage landings, a crucial aspect of SpaceX's cost-saving strategy
https://github.com/vishal-038/datascience_capstone_project

data-science jupyter-notebook k-means-clustering machine-learning python

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SpaceX Falcon 9 First Stage Landing Prediction Our project focuses on predicting the success of Falcon 9 first-stage landings, a crucial aspect of SpaceX's cost-saving strategy

• Host: GitHub
• URL: https://github.com/vishal-038/datascience_capstone_project
• Owner: VISHAL-038
• Created: 2024-05-23T05:05:59.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-05-27T16:14:24.000Z (7 months ago)
• Last Synced: 2024-05-28T00:33:30.364Z (7 months ago)
• Topics: data-science, jupyter-notebook, k-means-clustering, machine-learning, python
• Language: Jupyter Notebook
• Homepage:
• Size: 20.5 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# SpaceX Falcon 9 First Stage Landing Prediction Capstone

## Introduction

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.

### Module 1: Introduction

- Overview of the problem and tools needed for the course

### Module 2: Exploratory Data Analysis (EDA)

- Collecting data on Falcon 9 first-stage landings using a RESTful API and web scraping

- Converting data into a dataframe and performing data wrangling

### Module 3: Interactive Visual Analytics and Dashboard

- Building a dashboard to analyze launch records interactively with Plotly Dash

- Building an interactive map to analyze the launch site proximity with Folium

### Module 4: Predictive Analysis (Classification)

- Using machine learning to determine if the first stage of Falcon 9 will land successfully

- Splitting data into training data and test data to find the best Hyperparameter for SVM, Classification Trees, and Logistic Regression

- Finding the method that performs best using test data