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  3. Yale/UNC-CH - Geophysical Waveform Inversion
KaggleGeneral MLAdvancedRegistration closed

Yale/UNC-CH - Geophysical Waveform Inversion

A advanced general ml competition requiring roughly 25–70 hours for an end-to-end practice run.

Difficulty
Advanced
Estimated effort
25–70 hours
Registration deadline
Jun 23, 2025
Compute
CPU only
OverviewPreparationSource

Overview

Who this competition fits

Advanced practitioners with experience in general machine learning. Requires strong technical foundations and comfort with complex ML pipelines.

Read the original official blurb
Develop physics-guided machine learning models to solve full-waveform inversion problems

Preparation

From registration to a first submission

  1. 01

    Python

  2. 02

    scikit-learn or similar ML library

  3. 03

    data analysis with pandas

Before you commit: Requires solid machine learning fundamentals and good experimental methodology. The competitive landscape is strong, with many experienced teams.

Source

How this page was assembled

Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.

Official competition page
Kaggle
Last checked
Apr 8, 2025

Entry assessment

est.
22

Prepare before joining

Overall fit estimate

Beginner fit22/100
Learning value67/100

Confirm eligibility and time commitment before moving into formal preparation.

18+ · Location rules

Open official pageSign in to saveOpen guide

Timeline

Registration opens
Apr 8, 2025
Registration deadline
Jun 23, 2025
Submission deadline
Jun 30, 2025
Competition ends
Jun 30, 2025

Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win.

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Source page verifiedMetric confirmedReviewed
Source published
Apr 8, 2025
Source created
Oct 7, 2022
Published on this site
Jul 18, 2026