/machine-learning-challenge

Development of machine learning models capable of classifying candidate exoplanets from the raw dataset.

Primary LanguageJupyter NotebookMIT LicenseMIT

Machine Learning Homework - Exoplanet Exploration

exoplanets.jpg

Background

Over a period of nine years in deep space, the NASA Kepler space telescope has been out on a planet-hunting mission to discover hidden planets outside of our solar system.

To help process this data, you will create machine learning models capable of classifying candidate exoplanets from the raw dataset.

In this homework assignment, you will need to:

  1. Preprocess the raw data
  2. Tune the models
  3. Compare two or more models

Instructions

Preprocess the Data

  • Preprocess the dataset prior to fitting the model.
  • Perform feature selection and remove unnecessary features.
  • Use MinMaxScaler to scale the numerical data.
  • Separate the data into training and testing data.

Tune Model Parameters

  • Use GridSearch to tune model parameters.
  • Tune and compare at least two different classifiers.

Reporting

  • Create a README that reports a comparison of each model's performance as well as a summary about your findings and any assumptions you can make based on your model (is your model good enough to predict new exoplanets? Why or why not? What would make your model be better at predicting new exoplanets?).

Resources