CA Astro - Data Science and ML Workshop

This set of tutorials can be best explained as:

Tutorials and notebooks dedicated towards teaching about Data Science and Machine Learning

Main Details

Author Victor Calderon -
Dates 13th and 14th of June, 2020
Github Repo
Open In Colab


The following set of tutorials form part of the Tutorials Series hosted by “Central American - Caribbean Bridge in Astrophysics Program”.

In these tutorials, we will cover how to:

  • Extract datasets
  • Perform exploratory data analysis (EDA) of the datasets. This includes
    1. Extract summary statistics about the dataset
    2. Clean the datasets
    3. Transform columns to useful features
  • Define and train a machine learning (ML) model using out-of-the-box utilities from Python packages.
  • Determine the performance of the ML model

We will also discuss some common practices when dealing with ML models, as EDA best practices.