# Blog
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* __Distributed Deep Learning__
  <br>[BigDL: Distributed Deep Learning on Apache Spark](https://www.intel.com/content/www/us/en/developer/articles/technical/bigdl-distributed-deep-learning-on-apache-spark.html)
  <br>[BigDL: A Distributed Deep-Learning Framework for Big Data](https://arxiv.org/pdf/1804.05839.pdf)
* __Cluster Serving__
  <br>[Distributed Inference Made Easy with BigDL/Analytics Zoo Cluster Serving](https://www.intel.com/content/www/us/en/developer/articles/technical/distributed-inference-made-easy-with-analytics-zoo-cluster-serving.html)
 * __RayOnSpark__
  <br>[Run Emerging AI Applications on Big Data Clusters with Ray and BigDL & Analytics Zoo](https://medium.com/riselab/rayonspark-running-emerging-ai-applications-on-big-data-clusters-with-ray-and-analytics-zoo-923e0136ed6a)
  <br>[Build End-to-End AI Pipelines Using Ray and Apache Spark](https://medium.com/distributed-computing-with-ray/build-end-to-end-ai-pipeline-using-ray-and-apache-spark-23f70f36115e)
* __AutoML__
 <br>[Scalable AutoML for Time-Series Prediction Using Ray and BigDL & Analytics Zoo](https://medium.com/riselab/scalable-automl-for-time-series-prediction-using-ray-and-analytics-zoo-b79a6fd08139)
 <br>[Scalable AutoXGBoost Using Analytics Zoo](https://medium.com/intel-analytics-software/scalable-autoxgboost-using-analytics-zoo-automl-30d576cb138a)
* __Chronos__
 <br>[From Ray to Chronos: Build end-to-end AI use cases using BigDL on top of Ray](https://www.anyscale.com/blog/from-ray-to-chronos-build-end-to-end-ai-use-cases-using-bigdl-on-top-of-ray)
* __Performance__ 
<br>[Accelerating Deep-Learning Training with BigDL and Drizzle on Apache Spark](https://rise.cs.berkeley.edu/blog/accelerating-deep-learning-training-with-bigdl-and-drizzle-on-apache-spark)