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  3. 飞桨学习赛:个贷违约预测
Baidu AI StudioTime SeriesBeginnerRegistration unverified

飞桨学习赛:个贷违约预测

A beginner time series competition requiring roughly 4–12 hours for an end-to-end practice run.

Difficulty
Beginner
Estimated effort
4–12 hours
Registration deadline
To be confirmed
Compute
CPU only
OverviewResourcesPreparationSource

Overview

Who this competition fits

适合已有 Python 深度学习基础、愿意使用 PaddlePaddle 2.0+ 处理结构化信贷数据的个人参赛者。参赛者应能理解贷款金额、利率、还款、信用记录等字段,并完成贷款违约的二分类预测。

Read the original official blurb
本赛题要求选手利用已有的与目标客群稍有差异的另一批信贷数据,辅助目标业务风控模型的创建,希望大家可以利用迁移学习捕捉不同业务中用户基本信息与违约行为之间的关联,帮助实现对新业务的用户违约预测。 Official tags: 二分类问题. Sign-ups: 1649.

Resources

What this competition gives you

Taken from the competition's official page.

  • DataLoan-default training and test CSV datasets
  • TutorialFeatured learning project by 笠雨聆月

Preparation

From registration to a first submission

  1. 01

    PaddlePaddle 2.0+

  2. 02

    结构化表格数据处理

  3. 03

    贷款风控特征工程

  4. 04

    二分类预测模型

  5. 05

    AUC 优化

  6. 06

    CSV 提交文件生成

Before you commit: 核心难点是从两类贷款记录中大量数值、类别、日期、文本及匿名特征提取有效信号,并针对 AUC 优化违约预测。除预测文件外,还必须提交用 PaddlePaddle 训练的端到端模型对应的原始代码,且每天评测提交受限。

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
Baidu AI Studio
Last checked
Not recorded

Entry assessment

est.
78

Worth shortlisting

Overall fit estimate

Beginner fit78/100
Learning value72/100

Confirm eligibility and time commitment before moving into formal preparation.

Entry eligibility needs official confirmation

Open official pageSign in to saveOpen guide

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
Published on this site
Jul 21, 2026

Official metric is not published on the Baidu AI Studio competition listing; verify scoring on the competition page.