Beginner score
22/100
Competition workspace
适合有分子信息学或生物计算背景、能从SMILES构建分子表示并训练深度学习模型的开发者。参赛者还需要能够使用PaddlePaddle完成端到端模型训练，并准备可独立运行的预测代码；个人和最多5人的团队均可参赛。
Suggested next step
Decide whether this contest fits your current stage before you sink time into the leaderboard.
Beginner score
22/100
Learning value
58/100
Estimated effort
30-90 hours
Metric
Official scoring is published on the Ba…
适合有分子信息学或生物计算背景、能从SMILES构建分子表示并训练深度学习模型的开发者。参赛者还需要能够使用PaddlePaddle完成端到端模型训练，并准备可独立运行的预测代码；个人和最多5人的团队均可参赛。
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
SMILES分子表示
分子图表示学习
量子化学性质预测
PaddlePaddle 2.2+
OOD泛化建模
Python推理脚本与CSV输出
The real friction is usually not library usage. It is validation, time allocation, and task framing.
难点是训练数据有限，而测试分子与训练集在化学相似度和属性相似度上都被刻意拉开，模型必须同时应对结构外推和属性外推。复赛还要求提交可复现的压缩包：顶层含predict.py，并在指定环境与资源限制内读取多种测试文件、输出覆盖全部分子的result.csv。
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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Official metric is not published on the Baidu AI Studio competition listing; verify scoring on the competition page.