The Competition's detail can be find here
Basically the competition is about analyzing users' behaviors and messages they post on the Chinese micro-blog platform, and predicting the number of forwarding, comment and like on each message.
This project mainly use python and pandas.
The Stage 2 of this competition is still ongoing. Here is the data pipline I built for Stage 1.
This is a self-designed data pipline. The main thought is modularizing the process of a data project.
- User write methods to generate features, which stored as DataFrame in Pandas in features folder, and the feature.log will automatically record all existing features and their parameters.
- User can combine different features and select different models in the Train method, the model will be store in models folder, the model's information will be stored in train.log.
- User choose different combination of features and parameters for testing, the results will be store in results folder and the test information will be stored at test.log
- Ipython notebooks in notebooks folder is for playing around data, watching logs iteratively.
- The code locate in weiboPredict package.
When I do data project before, the problems of managing different version of features, models, results and naming them differently are killing me. This simple data pipeline solve my problem, cheers!
Sadly, the second stage of the competition is on Alibaba's ODPS platform with SQL and java, I don't have the chance to develop this framework further right now. The pipeline is still a little problem-specific and I want to build it for more general purpose in the furture.