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Astroraf/README.md

Hi, I'm Rafael Ferreira

A Data Scientist with background in Astrophysics

hello_there

👨🏽‍🔬  About Me

  • 👨🏽‍🦱 Pronouns, He/Him
  • 🤩 Favorite Language: Python 🐍
  • 🔬 Currently learning: 🧠 Neural Networks and Portuguese 🇵🇹
  • 🪐 Love of all things science, and always willing to collobrate
  • 🤝 I’m looking to collaborate on projects that will change the world for the better

🛠  Tech Stack

  • 👾 Python POSTGRESQL MSExcel Jupyter

  • ⚙️   Git GitHub Markdown

  • 💻   Windows iOS Conda Anaconda VSC


🪐 Recent Projects

Binary classification prediction model using NASA exoplanet archive database to predict wether the exoplanets discovered lie within their habitabale zones. Various features from the host star and exoplanet used to determine habitlity.

Libraries Utilized: Sckit-Learn, Pandas, Astropy, Numpy, Matpotlib, Seaborn, Scipy, Imblearn, bs4

Time series data set from NASA CO2 dataset that was recorded on weekly basis by scientist recorded in ppm as global average.Utilizing ARIMA, ARMA, and SARIMA models to make future predictions if CO2 levels stay the same

Libraries Utilized: Sckit-Learn, Pandas, Numpy, Matplotlib, Seaborn, StatsModel

Using various features about the home, location, and proximity to certain favorable locations, a linear regression model was used to created the most accurate prediction of these house in Kiings County, WA, USA. Accuracy was improved using feature engineering, one-hot encoding, and feature selction.

Libraries Utilized: Sckit-Learn, Pandas, Numpy, Matplotlib, Seaborn

Exploration of data in Yelp's API to help businesses determine where to setup a business. In this specific case, the option of opening a Yoga studio in either New York City or London. First immersive project for the Flatiron School Data Science Immersive Program.

Libraries Utilized: Pandas, Numpy, Matplotlib, Seaborn

🔌  Connect with Me


LinkedIn  Twitter  Medium  Gmail 

My Statistics


stats card guy


visitors


Credit: Rafael Ferreira

Last edited on: 02/09/2022

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