BigDL Documentation
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`BigDL <https://github.com/intel-analytics/BigDL/>`_ makes it easy for data scientists and data engineers to build end-to-end, distributed AI applications. The **BigDL 2.0** release combines the `original BigDL <https://github.com/intel-analytics/BigDL/tree/branch-0.14>`_ and `Analytics Zoo <https://github.com/intel-analytics/analytics-zoo>`_ projects, providing the following features:

* `DLlib <doc/DLlib/Overview/dllib.html>`_: distributed deep learning library for Apache Spark
* `Orca <doc/Orca/Overview/orca.html>`_: seamlessly scale out TensorFlow and PyTorch pipelines for distributed Big Data
* `RayOnSpark <doc/Ray/Overview/ray.html>`_: run Ray programs directly on Big Data clusters
* `Chronos <doc/Chronos/Overview/chronos.html>`_: scalable time series analysis using AutoML
* `PPML <doc/PPML/Overview/ppml.html>`_: privacy preserving big data analysis and machine learning (*experimental*)
* `Nano <doc/Nano/Overview/nano.html>`_: automatically accelerate TensorFlow and PyTorch pipelines by applying modern CPU optimizations
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