Analytics Zoo Documentation

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Analytics Zoo is an open source Big Data AI platform, and includes the following features for scaling end-to-end AI to distributed Big Data:

• Orca: seamlessly scale out TensorFlow and PyTorch for Big Data (using Spark & Ray)

• RayOnSpark: run Ray programs directly on Big Data clusters

• BigDL Extensions: high-level Spark ML pipeline and Keras-like APIs for BigDL

• Chronos: scalable time series analysis using AutoML

• PPML: privacy preserving big data analysis and machine learning (experimental)

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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
• RayOnSpark User Guide
• Chronos User Guide
• PPML User Guide
• Developer Guide

Common Use Case

• Use torch.distributed in Orca
• Use Spark Dataframe for Deep Learning
• Use Distributed Pandas for Deep Learning
• Use AutoTSEstimator for Time-Series Forecasting
• Use TSDataset and Forecaster for Time-Series Forecasting
• Use Anomaly Detector for Unsupervised Anomaly Detection
• Use Keras-Like API for BigDL
• Use Spark ML Pipeline for BigDL
• Enable AutoML for PyTorch
• Use AutoXGBoost to auto-tune XGBoost parameters

Orca Overview

• The Orca Library
• Orca Context
• Distributed Data-Parallel Processing
• Distributed Training and Inference
• Distributed Hyper-parameter Tuning

Python API

• Orca API
• AutoML API
• Friesian Feature API
• Chronos API

Real-World Application

• Presentations
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