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Quick Start

TensorFlow 1.15 Quickstart
Keras 2.3 Quickstart
TensorFlow 2 Quickstart
PyTorch Quickstart
RayOnSpark Quickstart

User Guide

Python User Guide
Scala User Guide
Colab User Guide
Docker User Guide
Hadoop/YARN User Guide
K8s User Guide
Databricks User Guide
Developer Guide

Nano Overview

Nano User Guide
Windows User Guide
BigDL-Nano PyTorch Training Overview
BigDL-Nano PyTorch Inference Overview
- Runtime Acceleration
- Quantization
BigDL-Nano TensorFlow Training Overview
BigDL-Nano TensorFlow Inference Overview
AutoML Overview

DLlib Overview

DLlib User Guide
Keras-Like API
Spark ML Pipeline Support

Orca Overview

The Orca Library
Orca Context
Distributed Data Processing
Distributed Training and Inference
Distributed Hyper-Parameter Tuning
RayOnSpark

Chronos Overview

Chronos User Guide
Chronos Deep Dive
Chronos Tutorial
Chronos Known Issue

PPML Overview

Privacy Preserving Machine Learning (PPML) User Guide
Trusted Big Data Analytics and ML
Trusted FL (Federated Learning)
Building Linux Kernel from Source with SGX Enabled
Deploy the Intel SGX Device Plugin for Kubernetes
Trusted Cluster Serving with Graphene on Kubernetes
TPC-H with Trusted SparkSQL on Kubernetes
TPC-DS with Trusted SparkSQL on Kubernetes

Serving Overview

Cluster Serving User Guide
Cluster Serving Quick Start
Install Cluster Serving
Start Cluster Serving
Inference by Cluster Serving
Cluster Serving Example
Cluster Serving FAQ
Contribute to Cluster Serving

Common Use Case

Use torch.distributed in Orca
Use Spark Dataframe for Deep Learning
Use Distributed Pandas for Deep Learning
Enable AutoML for PyTorch
Use AutoXGBoost to auto-tune XGBoost parameters

Python API

Orca API
Friesian Feature API
Chronos API

Real-World Application

Presentations
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BigDL-Nano PyTorch Inference Overview
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BigDL-Nano PyTorch Inference Overview¶

add a link for examples here.

Runtime Acceleration¶

onnx runtime, openvino

Quantization¶

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