Beginner score
78/100
Competition workspace
适合已有结构化订单数据建模经验、愿意使用 PaddlePaddle 2.0 及以上版本的个人参赛者。参赛者应能从用户、订单、商品及付款时间等字段构建特征，并输出用户下个月是否购买的预测概率。
Suggested next step
Decide whether this contest fits your current stage before you sink time into the leaderboard.
Beginner score
78/100
Learning value
72/100
Estimated effort
4-12 hours
Metric
Official scoring is published on the Ba…
适合已有结构化订单数据建模经验、愿意使用 PaddlePaddle 2.0 及以上版本的个人参赛者。参赛者应能从用户、订单、商品及付款时间等字段构建特征，并输出用户下个月是否购买的预测概率。
Taken from the competition's official page.
Historical order training data and next-month purchase test data
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
PaddlePaddle 2.0+
订单数据特征工程
时间滑窗特征
二分类概率预测
AUC 优化
AI Studio Notebook 提交
The real friction is usually not library usage. It is validation, time allocation, and task framing.
主要难点是从经过模拟生成、部分特征含义被隐藏且脱敏的历史订单记录中提取有效的用户购买信号，尤其需要处理付款时间并构造时间滑窗特征。还需在 AI Studio Notebook 中通过命令和 token 提交预测结果及可能要求的源码。
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.
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Rules, files, submission details, and the live deadline still come from the official page.
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Official metric is not published on the Baidu AI Studio competition listing; verify scoring on the competition page.