Welcome to Final Proyect of Data Science on Coursera

The objective of the course is to train a model with supervised learning to establish the success or failure of landing the first stage of the Falcon 9 for a fictitious company. To do this, data from a SpaceX API and web scarping were used. In this work you will find the parts that make up a data science project itself. From data collection, cleaning, visualization and model training

Index

• API Scraping (jupyter-labs-spacex-data-collection-api)
• Web Scraping (webscrapingCapstone) - Exploring and Preparing data (edadataviz)
• MySQL Data Exploration (Jupyter-labs-eda-sql-sqlite..)
• Interactive Visual Analytics with Folium (lab_jupyter_launch_site_location.ipynb)

Machine Learning Prediction lab

SpaceX_Machine Learning Prediction_Part_5(1)

• Machine Learning prediction with Logistic Regression
• Machine Learning prediction with SVC
• Machine Learning prediction with Decision Tree Classifier
• Machine Learning prediction with k nearest neighbors

Technology

The following libraries are used in this laboratory:

• Pandas
• Numpy
• seaborn
• Folium
• Sklearn
• datetime
• BeatifulSoup package
• SQL and MySQL language