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This project is part of the IBM Data Science Professional Certificate course. It aims to identify the best classifier to predict whether the first stage of a Falcon9 rocket will land successfully, helping SpaceX minimize costs.

Python 0.41% Jupyter Notebook 99.59%

data-science-capstone-project's Introduction

Data Science Capstone Project (Choosing the best classifier)

This project is a part of the IBM Data Science Professional Certificate course

Objective

The purpose of this project is to find the best classifier to predict if the first stage of Falcon9 rocket will land successfully or not which in-turn can be used to determine and minimize the cost by SpaceX.

Methods Used

Web Scraping
Data Wrangling
Exploratory Data Analysis
Data Visualization
Machine Learning

Technologies used

Python
SQL
Jupyter

Stages

Data Collection - Data is collected using API integration with SpaceX API and by using BeautifulSoup library to scrape data from Wikipedia
Data Wrangling - After collecting the required data, data is cleaned and made useful for further analysis
Exploratory Data Analysis - Data is now analysed using various statistical techniques and using SQL to get to know more about the data for further stages of the project
Data Visualization - Data is analyzed using various visualization techniques to get a deep understanding of data to use various features of data effectively in model creation
Machine Learning - Now data is standardized and separated into train and test data to be used in various models and then finding the best hyperparameter to be used in various models, now using these parameters to find the best performing classifier.

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