https://github.com/adrianmarino/knn-cf-rec-sys
Similarity CF based RecSys examples
https://github.com/adrianmarino/knn-cf-rec-sys
python recommender-system scikit-learn
Last synced: about 2 months ago
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Similarity CF based RecSys examples
- Host: GitHub
- URL: https://github.com/adrianmarino/knn-cf-rec-sys
- Owner: adrianmarino
- Created: 2022-03-05T19:36:48.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-05-30T22:20:49.000Z (about 4 years ago)
- Last Synced: 2025-09-07T04:39:07.618Z (10 months ago)
- Topics: python, recommender-system, scikit-learn
- Language: Jupyter Notebook
- Homepage:
- Size: 1.49 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Collaborative filtering KNN based recommendation systems
Similarity collaborative filtering based RecSys.
[Notebook](https://github.com/adrianmarino/cf-rec-sys-examples/blob/master/notebooks/knn-cf-rec-sys.ipynb)
## Sources
* **Collaborative filtering**
* [Medium: Collaborative Filtering based Recommendation Systems exemplified..](https://towardsdatascience.com/collaborative-filtering-based-recommendation-systems-exemplified-ecbffe1c20b1)
* This project is base in: [CF Recommendation System-Examples.ipynb](https://github.com/csaluja/JupyterNotebooks-Medium/blob/master/CF%20Recommendation%20System-Examples.ipynb)
* **Metrics**
* [Precision@k: The Overlooked Metric for Fraud and Lead Scoring Models](https://towardsdatascience.com/precision-k-the-overlooked-metric-for-fraud-and-lead-scoring-models-fabad2893c01)
* [Popular evaluation metrics in recommender systems explained](https://medium.com/qloo/popular-evaluation-metrics-in-recommender-systems-explained-324ff2fb427d)
* [How mean Average Precision at k (mAP@k) can be more useful than other evaluation metrics](https://medium.com/@misty.mok/how-mean-average-precision-at-k-map-k-can-be-more-useful-than-other-evaluation-metrics-6881e0ee21a9)
## Getting started
**Step 1**: Clone repo.
```bash
$ git clone https://github.com/adrianmarino/knn-cf-rec-sys.git
$ cd knn-cf-rec-sys
```
**Step 2**: Create environment.
```bash
$ conda env create -f environment.yml
```
## Open notebooks locally
**Step 1**: Enable project environment.
```bash
$ conda activate knn-cf-rec-sys
```
**Step 2**: Under project directory boot jupyter lab.
```bash
$ jupyter lab
Jupyter Notebook 6.1.4 is running at:
http://localhost:8888/?token=45efe99607fa6......
```
**Step 3**: Go to http://localhost:8888.... as indicated in the shell output.