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| .. | ||
| reco_utils | ||
| scripts | ||
| README.md | ||
| dkn_synthetic.ipynb | ||
| fastai_movielens.ipynb | ||
| ncf_movielens.ipynb | ||
| rbm_movielens.ipynb | ||
| sar_movielens.ipynb | ||
| wide_deep_movielens.ipynb | ||
| xdeepfm_synthetic.ipynb | ||
README.md
Run your notebooks as-is on AzureML Service
This folder demonstrates how to build, train and test notebooks from our Recommendation Project project so you can make your own Recommendation system.
We use MLOps to manually or automatically trigger builds due to Github PRs and changes. The control plane is in DevOps and AzureML Service provides numerous capabilities to track your assets when running Jupyter notebooks local or in the cloud.