Beginner score
18/100
Competition workspace
Advanced practitioners with experience in general machine learning. Requires strong technical foundations and comfort with complex ML pipelines.
Suggested next step
Decide whether this contest fits your current stage before you sink time into the leaderboard.
Beginner score
18/100
Learning value
65/100
Estimated effort
25-70 hours
Metric
Official scoring is published on the Op…
Advanced practitioners with experience in general machine learning. Requires strong technical foundations and comfort with complex ML pipelines.
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
Python
scikit-learn or similar ML library
data analysis with pandas
The real friction is usually not library usage. It is validation, time allocation, and task framing.
Requires solid machine learning fundamentals and good experimental methodology. The competitive landscape is strong, with many experienced teams.
This guide is the best pre-read if you want a cleaner start instead of trial-and-error.
How to learn feature engineering, validation, and competition workflow without heavy hardware.
No GPU? Pick Competitions That Still Teach You Good HabitsUse these fields to make a quick decision before you dive deeper.
Registration is unverified; confirm availability on the official page before investing.
Sign in to save competitions and build your own shortlist.
Rules, files, submission details, and the live deadline still come from the official page.
These competitions share a similar domain or difficulty level.
ModelScope
General MLModelScope
General MLKaggle
General MLKaggle
General MLSeparate what is confirmed from what still needs review. Official rules and deadlines win — report anything that looks wrong.
Official metric is not published on the OpenAtom competition listing; verify scoring on the competition page.
reward_value_usd is a rough CNY→USD estimate (×0.14) for ranking only; use reward_summary for the official prize text.