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README.md
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</div> </div>
--- ---
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: 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](#getting-started-with-dllib): distributed deep learning library for Apache Spark *(i.e., the original BigDL framework with Keras-style API and Spark ML pipeline support)* * [DLlib](#getting-started-with-dllib): distributed deep learning library for Apache Spark *(i.e., the original BigDL framework with Keras-style API and Spark ML pipeline support)*

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docs/readthedocs/source/doc/DLlib/Overview/dllib.md
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# DLlib User Guide # DLlib User Guide
## 1. Overview
DLlib is a distributed deep learning library for Apache Spark; with DLlib, users can write their deep learning applications as standard Spark programs (using either Scala or Python APIs). DLlib is a distributed deep learning library for Apache Spark; with DLlib, users can write their deep learning applications as standard Spark programs (using either Scala or Python APIs).
It includes the functionalities of the original [BigDL](https://github.com/intel-analytics/BigDL/tree/branch-0.14) project, and provides following high-level APIs for distributed deep learning on Spark: It includes the functionalities of the [original BigDL](https://github.com/intel-analytics/BigDL/tree/branch-0.14) project, and provides following high-level APIs for distributed deep learning on Spark:
* [Keras-like API](keras-api.md) * [Keras-like API](keras-api.md)
* [Spark ML pipeline support](nnframes.md) * [Spark ML pipeline support](nnframes.md)
## 2. Scala user guide
### 2.1 Install
### 2.2 Run
### 2.3 Get started (example)
## 3. Python user guide
### 3.1 Install
### 3.2 Run
### 3.3 Get started (example)

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docs/readthedocs/source/index.rst
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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: `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 * `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 * `Orca <doc/Orca/Overview/orca.html>`_: seamlessly scale out TensorFlow and PyTorch pipelines for distributed Big Data