Skip to content

Commit 73123c9

Browse files
darrylongtqtg
andauthored
Update Readme to include Cornac-AB section (#638)
* Add Cornac-AB section to Readme.md * Update README.md * Update assets directory and downsized images --------- Co-authored-by: Tuan Truong <[email protected]>
1 parent 163c315 commit 73123c9

File tree

5 files changed

+9
-1
lines changed

5 files changed

+9
-1
lines changed

README.md

Lines changed: 9 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -63,7 +63,7 @@ brew install gcc | brew link gcc
6363

6464
## Getting started: your first Cornac experiment
6565

66-
![](flow.jpg)
66+
![](assets/flow.jpg)
6767
<p align="center"><i>Flow of an Experiment in Cornac</i></p>
6868

6969
```python
@@ -125,6 +125,14 @@ $ curl -X GET "http://localhost:8080/recommend?uid=63&k=5&remove_seen=false"
125125
```
126126
If we want to remove seen items during training, we need to provide `TRAIN_SET` which has been saved with the model earlier, when starting the serving app. We can also leverage [WSGI](https://flask.palletsprojects.com/en/3.0.x/deploying/) server for model deployment in production. Please refer to [this](https://cornac.readthedocs.io/en/stable/user/iamadeveloper.html#running-an-api-service) guide for more details.
127127

128+
## Model A/B testing
129+
130+
[Cornac-AB](https://github.com/preferredAI/cornac-ab) is an extension of Cornac using the Cornac Serving API. Easily create and manage A/B testing experiments to further understand your model performance with online users.
131+
132+
| User Interaction Solution | Recommendations Dashboard | Feedback Dashboard |
133+
|:------------------------:|:------------------------:|:------------------:|
134+
| <img src="assets/demo.png" alt="demo" width="250"/> | <img src="assets/recommendation-dashboard.png" alt="recommendations" width="250"/> | <img src="assets/feedback-dashboard.png" alt="feedback" width="250"/> |
135+
128136
## Efficient retrieval with ANN search
129137

130138
One important aspect of deploying recommender model is efficient retrieval via Approximate Nearest Neighbor (ANN) search in vector space. Cornac integrates several vector similarity search frameworks for the ease of deployment. [This example](tutorials/ann_hnswlib.ipynb) demonstrates how ANN search will work seamlessly with any recommender models supporting it (e.g., matrix factorization).

assets/demo.png

82.1 KB
Loading

assets/feedback-dashboard.png

38.9 KB
Loading
File renamed without changes.
41.3 KB
Loading

0 commit comments

Comments
 (0)