guoday/Tencent2020_Rank1st resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1085 stars · 319 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

The first-place winning solution code for the 2020 Tencent College Algorithm Contest, which predicts users' age and gender from 91 days of ad click history. It uses Word2Vec and BERT pretraining on click sequences with a fusion-layer classification model built in PyTorch.

Use cases

• predict user age and gender from ad click history
• learn how to win a machine learning competition
• pretrain BERT on behavioral click sequences
• apply word2vec embeddings to user behavior data
• study a top-ranked deep learning competition solution
• build a user demographic prediction model

When to choose

• you want a reference implementation for demographic prediction from click logs
• you are studying winning approaches for sequence-based ML competitions
• you need an example of domain-adaptive BERT pretraining on behavioral data

When to avoid

• you need a production-ready or maintained library
• you lack GPU resources and large memory
• you need a licensed, reusable codebase (no license is provided)

Facets

learning-resource · maturity maintenance

machine-learning deep-learning nlp data-science machine-learning artificial-intelligence data-science python kaggle-competition bert word2vec user-profiling age-gender-prediction click-through-rate competition-solution advertising linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="guoday/Tencent2020_Rank1st")