(In)Direct from the Source: A Xeek Challenge
Join our latest Xeek challenge to learn how to use Python to work with geoscience data.
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Picture it: you’ve been hired to explore for hydrocarbons in the Pluto Basin. You discover the legacy data for the basin is lacking, and what you do have is full of errors and different processing methodologies. It’s your job to figure out how to clean the data, generate synthetic data, and build anML model to predict oil families.
Never heard of the Pluto Basin? That might be because it doesn’t exist. Welcome to the imaginary site of our newest Xeek challenge: (In)Direct from the Source.
(In)Direct from the Source will teach you how to use Python to work with geoscience data. Through your work in the fictional Pluto Basin, you will create a foundation for further learning with the help of simple tools and methods. These include:
- Cleaning and normalizing a table of data
- Creating a synthetic training set based on sampling real data
- Building a simple ML model
A starter notebook will walk you through the process of building aML model in Python, step by step. You’ll get to hone your data science skills and in the end you can submit your predictions on Xeek as CSV files to get a score showing how close you are to the actual answer.
Head over to get a more detailed look at the (In)Direct from theSource challenge and join. It’s great for beginners, and includes $2k in prizes. Best of luck in the Pluto Basin!
Join the challenge here: https://xeek.ai/challenges/in-direct-from-the-source/overview