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README.md


A unified Data Analytics and AI platform for distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray


What is Analytics Zoo?

Analytics Zoo seamless scales TensorFlow, Keras and PyTorch to distributed big data (using Spark, Flink & Ray).


  • End-to-end pipeline for applying AI models (TensorFlow, PyTorch, OpenVINO, etc.) to distributed big data

    • Write TensorFlow or PyTorch inline with Spark code for distributed training and inference.
    • Native deep learning (TensorFlow/Keras/PyTorch/BigDL) support in Spark ML Pipelines.
    • Directly run Ray programs on big data cluster through RayOnSpark.
    • Plain Java/Python APIs for (TensorFlow/PyTorch/BigDL/OpenVINO) Model Inference.
  • High-level ML workflow for automating machine learning tasks

    • Cluster Serving for automatically distributed (TensorFlow/PyTorch/Caffe/OpenVINO) model inference .
    • Scalable AutoML for time series prediction.
  • Built-in models for Recommendation, Time Series, Computer Vision and NLP applications.


Why use Analytics Zoo?

You may want to develop your AI solutions using Analytics Zoo if:

  • You want to easily apply AI models (e.g., TensorFlow, Keras, PyTorch, BigDL, OpenVINO, etc.) to distributed big data.
  • You want to transparently scale your AI applications from a single laptop to large clusters with "zero" code changes.
  • You want to deploy your AI pipelines to existing YARN or K8S clusters WITHOUT any modifications to the clusters.
  • You want to automate the process of applying machine learning (such as feature engineering, hyperparameter tuning, model selection, distributed inference, etc.).

How to use Analytics Zoo?

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