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@ -19,7 +19,7 @@ BigDL makes it easy for data scientists and data engineers to build end-to-end,
* [PPML](#ppml-privacy-preserving-machine-learning): privacy preserving big data analysis and machine learning (*experimental*) * [PPML](#ppml-privacy-preserving-machine-learning): privacy preserving big data analysis and machine learning (*experimental*)
* [Serving](#getting-started-with-serving): Distributed and Automated Model Inference on Big Data Streaming Frameworks * [Cluster Serving](https://bigdl.readthedocs.io/en/latest/doc/Serving/Overview/serving.html): Real-time, Distributed Model Serving
For more information, you may [read the docs](https://bigdl.readthedocs.io/). For more information, you may [read the docs](https://bigdl.readthedocs.io/).
@ -201,13 +201,6 @@ See the Chronos [user guide](https://bigdl.readthedocs.io/en/latest/doc/Chronos/
See the [PPML user guide](https://bigdl.readthedocs.io/en/latest/doc/PPML/Overview/ppml.html) for more details. See the [PPML user guide](https://bigdl.readthedocs.io/en/latest/doc/PPML/Overview/ppml.html) for more details.
## Getting Started with Serving
BigDL Cluster Serving is an end-to-end pipeline to scale-out local applications. We recommend you to refer to following example to kick-off.
[Migrate Keras application to Serving](https://bigdl.readthedocs.io/en/latest/doc/Serving/Example/keras-to-cluster-serving-example.ipynb)
See the Serving [user guide](https://bigdl.readthedocs.io/en/latest/doc/Serving/Overview/serving.html) and [quickstart](https://bigdl.readthedocs.io/en/latest/doc/Serving/QuickStart/serving-quickstart.html) for more details.
## More information ## More information
- [Document Website](https://bigdl.readthedocs.io/) - [Document Website](https://bigdl.readthedocs.io/)