kopia lustrzana https://github.com/twitter/the-algorithm
15 wiersze
979 B
Markdown
15 wiersze
979 B
Markdown
# Notification Light Ranker Model
|
||
|
||
## Model Context
|
||
There are 4 major components of Twitter notifications recommendation system: 1) candidate generation 2) light ranking 3) heavy ranking & 4) quality control. This notification light ranker model bridges candidate generation and heavy ranking by pre-selecting highly-relevant candidates from the initial huge candidate pool. It’s a light-weight model to reduce system cost during heavy ranking without hurting user experience.
|
||
|
||
## Directory Structure
|
||
- BUILD: this file defines python library dependencies
|
||
- model_pools_mlp.py: this file defines tensorflow model architecture for the notification light ranker model
|
||
- deep_norm.py: this file contains 1) how to build the tensorflow graph with specified model architecture, loss function and training configuration. 2) how to set up the overall model training & evaluation pipeline
|
||
- eval_model.py: the main python entry file to set up the overall model evaluation pipeline
|
||
|
||
|
||
|
||
|