Branch docs (#3677)
Co-authored-by: Kai Huang <huangkaivision@gmail.com>
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Blogs
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---
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**2021**
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- [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)
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- [Scalable AutoXGBoost Using Analytics Zoo AutoML](https://medium.com/intel-analytics-software/scalable-autoxgboost-using-analytics-zoo-automl-30d576cb138a)
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- [Intelligent 5G L2 MAC Scheduler: Powered by Capgemini NetAnticipate 5G on Intel Architecture](https://networkbuilders.intel.com/solutionslibrary/intelligent-5g-l2-mac-scheduler-powered-by-capgemini-netanticipate-5g-on-intel-architecture)
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- [Better Together: Privacy-Preserving Machine Learning Powered by Intel SGX and Intel DL Boost](https://www.intel.com/content/www/us/en/artificial-intelligence/posts/alibaba-privacy-preserving-machine-learning.html)
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**2020**
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- [SK Telecom, Intel Build AI Pipeline to Improve Network Quality](https://networkbuilders.intel.com/solutionslibrary/sk-telecom-intel-build-ai-pipeline-to-improve-network-quality)
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- [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)
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- [Tencent Cloud Leverages Analytics Zoo to Improve Performance of TI-ONE ML Platform](https://www.intel.com/content/www/us/en/developer/articles/technical/tencent-cloud-leverages-analytics-zoo-to-improve-performance-of-ti-one-ml-platform.html)
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- [Context-Aware Fast Food Recommendation at Burger King with RayOnSpark](https://medium.com/riselab/context-aware-fast-food-recommendation-at-burger-king-with-rayonspark-2e7a6009dd2d)
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- [Seamlessly Scaling AI for Distributed Big Data](https://medium.com/swlh/seamlessly-scaling-ai-for-distributed-big-data-5b589ead2434)
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- [Distributed Inference Made Easy with 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)
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**2019**
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- [BigDL: A Distributed Deep-Learning Framework for Big Data](https://arxiv.org/abs/1804.05839)
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- [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)
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- [RayOnSpark: 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)
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- [Real-time Product Recommendations for Office Depot Using Apache Spark and Analytics Zoo on AWS](https://www.intel.com/content/www/us/en/developer/articles/technical/real-time-product-recommendations-for-office-depot-using-apache-spark-and-analytics-zoo-on.html)
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- [Machine Learning Pipelines for High Energy Physics Using Apache Spark with BigDL and Analytics Zoo](https://db-blog.web.cern.ch/blog/luca-canali/machine-learning-pipelines-high-energy-physics-using-apache-spark-bigdl)
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- [Deep Learning with Analytic Zoo Optimizes Mastercard Recommender AI Service](https://www.intel.com/content/www/us/en/developer/articles/technical/deep-learning-with-analytic-zoo-optimizes-mastercard-recommender-ai-service.html)
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- [Using Intel Analytics Zoo to Inject AI into Customer Service Platform (Part II)](https://www.infoq.com/articles/analytics-zoo-qa-module/)
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- [Talroo Uses Analytics Zoo and AWS to Leverage Deep Learning for Job Recommendations](https://www.intel.com/content/www/us/en/developer/articles/technical/talroo-uses-analytics-zoo-and-aws-to-leverage-deep-learning-for-job-recommendations.html)
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**2018**
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- [Analytics Zoo: Unified Analytics + AI Platform for Distributed Tensorflow, and BigDL on Apache Spark](https://www.infoq.com/articles/analytics-zoo/)
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- [Industrial Inspection Platform in Midea and KUKA: Using Distributed TensorFlow on Analytics Zoo](https://www.intel.com/content/www/us/en/developer/articles/technical/industrial-inspection-platform-in-midea-and-kuka-using-distributed-tensorflow-on-analytics.html)
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- [Use Analytics Zoo to Inject AI Into Customer Service Platforms on Microsoft Azure](https://www.intel.com/content/www/us/en/developer/articles/technical/use-analytics-zoo-to-inject-ai-into-customer-service-platforms-on-microsoft-azure-part-1.html)
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- [LSTM-Based Time Series Anomaly Detection Using Analytics Zoo for Apache Spark and BigDL at Baosight](https://www.intel.com/content/www/us/en/developer/articles/technical/lstm-based-time-series-anomaly-detection-using-analytics-zoo-for-apache-spark-and-bigdl.html)
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**2017**
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- [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)
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- [Using BigDL to Build Image Similarity-Based House Recommendations](https://www.intel.com/content/www/us/en/developer/articles/technical/using-bigdl-to-build-image-similarity-based-house-recommendations.html)
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- [Building Large-Scale Image Feature Extraction with BigDL at JD.com](https://www.intel.com/content/www/us/en/developer/articles/technical/building-large-scale-image-feature-extraction-with-bigdl-at-jdcom.html)
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---
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**Tutorial:**
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- Seamlessly Scaling out Big Data AI on Ray and Apache Spark, [CVPR 2021](https://cvpr2021.thecvf.com/program) [tutorial](https://jason-dai.github.io/cvpr2021/), June 2021, ([slides](https://jason-dai.github.io/cvpr2021/slides/End-to-End%20Big%20Data%20AI%20Pipeline%20using%20Analytics%20Zoo%20-%20CVPR21.pdf))
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- Seamlessly Scaling out Big Data AI on Ray and Apache Spark, [CVPR 2021](https://cvpr2021.thecvf.com/program) [tutorial](https://jason-dai.github.io/cvpr2021/), June 2021 ([slides](https://jason-dai.github.io/cvpr2021/slides/End-to-End%20Big%20Data%20AI%20Pipeline%20using%20Analytics%20Zoo%20-%20CVPR21.pdf))
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- Automated Machine Learning Workflow for Distributed Big Data Using Analytics Zoo, [CVPR 2020](https://cvpr2020.thecvf.com/program/tutorials) [tutorial](https://jason-dai.github.io/cvpr2020/), June 2020, ([slides](https://jason-dai.github.io/cvpr2020/slides/AIonBigData_cvpr20.pdf))
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- Automated Machine Learning Workflow for Distributed Big Data Using Analytics Zoo, [CVPR 2020](https://cvpr2020.thecvf.com/program/tutorials) [tutorial](https://jason-dai.github.io/cvpr2020/), June 2020 ([slides](https://jason-dai.github.io/cvpr2020/slides/AIonBigData_cvpr20.pdf))
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- Building Deep Learning Applications for Big Data, [AAAI 2019]( https://aaai.org/Conferences/AAAI-19/aaai19tutorials/#sp2) [tutorial](https://jason-dai.github.io/aaai2019/), January 2019, ([slides](https://jason-dai.github.io/aaai2019/slides/AI%20on%20Big%20Data%20(Jason%20Dai).pdf))
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- Building Deep Learning Applications for Big Data, [AAAI 2019]( https://aaai.org/Conferences/AAAI-19/aaai19tutorials/#sp2) [tutorial](https://jason-dai.github.io/aaai2019/), January 2019 ([slides](https://jason-dai.github.io/aaai2019/slides/AI%20on%20Big%20Data%20(Jason%20Dai).pdf))
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- Analytics Zoo: Distributed TensorFlow and Keras on Apache Spark, [AI conference](https://conferences.oreilly.com/artificial-intelligence/ai-ca-2019/public/schedule/detail/77069), Sep 2019, San Jose ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/Tutorial%20Analytics%20ZOO.pdf))
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- Building Deep Learning Applications on Big Data Platforms, [CVPR 2018](https://cvpr2018.thecvf.com/) [tutorial](https://jason-dai.github.io/cvpr2018/), June 2018, ([slides](https://jason-dai.github.io/cvpr2018/slides/BigData_DL_Jason-CVPR.pdf))
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- Building Deep Learning Applications on Big Data Platforms, [CVPR 2018](https://cvpr2018.thecvf.com/) [tutorial](https://jason-dai.github.io/cvpr2018/), June 2018 ([slides](https://jason-dai.github.io/cvpr2018/slides/BigData_DL_Jason-CVPR.pdf))
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**Talks:**
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- Mobile Order Click-Through Rate (CTR) Recommendation with Ray on Apache Spark at Burger King, [Ray Summit 2021](https://www.anyscale.com/events/2021/06/22/mobile-order-click-through-rate-ctr-recommendation-with-ray-on-apache-spark-at-burger-king), June 2021, ([slides](https://files.speakerdeck.com/presentations/1870110b5adf4bfc8f0c76255a417f09/Kai_Huang_and_Luyang_Wang.pdf))
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- E2E Smart Transportation CV application in Inspur (using Insight Data-Intelligence platform), [CVPR 2021](https://jason-dai.github.io/cvpr2021/), July 2021 ([slides](https://jason-dai.github.io/cvpr2021/slides/Inspur%20E2E%20Smart%20Transportation%20CV%20application%20-CVPR21.pdf))
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- Deep Reinforcement Learning Recommenders using RayOnSpark, **Data + AI Summit 2021**, May 2021, ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/210527DeepReinforcementLearningRecommendersUsingRayOnSpark2.pdf))
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- Mobile Order Click-Through Rate (CTR) Recommendation with Ray on Apache Spark at Burger King, [Ray Summit 2021](https://www.anyscale.com/events/2021/06/22/mobile-order-click-through-rate-ctr-recommendation-with-ray-on-apache-spark-at-burger-king), June 2021 ([slides](https://files.speakerdeck.com/presentations/1870110b5adf4bfc8f0c76255a417f09/Kai_Huang_and_Luyang_Wang.pdf))
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- Cluster Serving: Deep Learning Model Serving for Big Data, **Data + AI Summit 2021**, May 2021, ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/210526Cluster-Serving.pdf))
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- Deep Reinforcement Learning Recommenders using RayOnSpark, **Data + AI Summit 2021**, May 2021 ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/210527DeepReinforcementLearningRecommendersUsingRayOnSpark2.pdf))
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- Offer Recommendation System with Apache Spark at Burger King, [Data + AI Summit 2021](https://databricks.com/session_na21/offer-recommendation-system-with-apache-spark-at-burger-king), May 2021, ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/20210526Offer%20Recommendation.pdf))
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- Cluster Serving: Deep Learning Model Serving for Big Data, **Data + AI Summit 2021**, May 2021 ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/210526Cluster-Serving.pdf))
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- Context-aware Fast Food Recommendation with Ray on Apache Spark at Burger King, [Data + AI Summit Europe 2020](https://databricks.com/session_eu20/context-aware-fast-food-recommendation-with-ray-on-apache-spark-at-burger-king), November 2020, ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/1118%20Context-aware%20Fast%20Food%20Recommendation%20with%20Ray%20on%20Apache%20Spark%20at%20Burger%20King.pdf))
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- Offer Recommendation System with Apache Spark at Burger King, [Data + AI Summit 2021](https://databricks.com/session_na21/offer-recommendation-system-with-apache-spark-at-burger-king), May 2021 ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/20210526Offer%20Recommendation.pdf))
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- Cluster Serving: Distributed Model Inference using Apache Flink in Analytics Zoo, [Flink Forward 2020](https://www.flink-forward.org/global-2020/conference-program#cluster-serving--distributed-model-inference-using-apache-flink-in-analytics-zoo), October 2020, ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/1020%20Cluster%20Serving%20Distributed%20Model%20Inference%20using%20Apache%20Flink%20in%20Analytics%20Zoo%20.pdf))
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- Context-aware Fast Food Recommendation with Ray on Apache Spark at Burger King, [Data + AI Summit Europe 2020](https://databricks.com/session_eu20/context-aware-fast-food-recommendation-with-ray-on-apache-spark-at-burger-king), November 2020 ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/1118%20Context-aware%20Fast%20Food%20Recommendation%20with%20Ray%20on%20Apache%20Spark%20at%20Burger%20King.pdf))
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- Project Zouwu: Scalable AutoML for Telco Time Series Analysis using Ray and Analytics Zoo, [Ray Summit Connect 2020](https://anyscale.com/blog/videos-and-slides-for-the-fourth-ray-summit-connect-august-12-2020/), August 2020, ([slides](https://anyscale.com/wp-content/uploads/2020/08/Ding-Ding-Connect-slides.pdf))
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- Cluster Serving: Distributed Model Inference using Apache Flink in Analytics Zoo, [Flink Forward 2020](https://www.flink-forward.org/global-2020/conference-program#cluster-serving--distributed-model-inference-using-apache-flink-in-analytics-zoo), October 2020 ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/1020%20Cluster%20Serving%20Distributed%20Model%20Inference%20using%20Apache%20Flink%20in%20Analytics%20Zoo%20.pdf))
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- Cluster Serving: Distributed Model Inference using Big Data Streaming in Analytics Zoo, [OpML 2020](https://www.usenix.org/conference/opml20/presentation/song), July 2020, ([slides](https://www.usenix.org/sites/default/files/conference/protected-files/opml20_talks_43_slides_song.pdf))
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- Project Zouwu: Scalable AutoML for Telco Time Series Analysis using Ray and Analytics Zoo, [Ray Summit Connect 2020](https://anyscale.com/blog/videos-and-slides-for-the-fourth-ray-summit-connect-august-12-2020/), August 2020 ([slides](https://anyscale.com/wp-content/uploads/2020/08/Ding-Ding-Connect-slides.pdf))
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- Scalable AutoML for Time Series Forecasting using Ray, [OpML 2020](https://www.usenix.org/conference/opml20/presentation/huang), July 2020, ([slides](https://www.usenix.org/sites/default/files/conference/protected-files/opml20_talks_84_slides_huang.pdf))
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- Cluster Serving: Distributed Model Inference using Big Data Streaming in Analytics Zoo, [OpML 2020](https://www.usenix.org/conference/opml20/presentation/song), July 2020 ([slides](https://www.usenix.org/sites/default/files/conference/protected-files/opml20_talks_43_slides_song.pdf))
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- Scalable AutoML for Time Series Forecasting using Ray, [Spark + AI Summit 2020](https://databricks.com/session_na20/scalable-automl-for-time-series-forecasting-using-ray), June 2020, ([slides](https://www.slideshare.net/databricks/scalable-automl-for-time-series-forecasting-using-ray))
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- Scalable AutoML for Time Series Forecasting using Ray, [OpML 2020](https://www.usenix.org/conference/opml20/presentation/huang), July 2020 ([slides](https://www.usenix.org/sites/default/files/conference/protected-files/opml20_talks_84_slides_huang.pdf))
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- Running Emerging AI Applications on Big Data Platforms with Ray On Apache Spark, [Spark + AI Summit 2020](https://databricks.com/session_na20/running-emerging-ai-applications-on-big-data-platforms-with-ray-on-apache-spark), June 2020, ([slides](https://www.slideshare.net/databricks/running-emerging-ai-applications-on-big-data-platforms-with-ray-on-apache-spark))
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- Scalable AutoML for Time Series Forecasting using Ray, [Spark + AI Summit 2020](https://databricks.com/session_na20/scalable-automl-for-time-series-forecasting-using-ray), June 2020 ([slides](https://www.slideshare.net/databricks/scalable-automl-for-time-series-forecasting-using-ray))
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- Vectorized Deep Learning Acceleration from Preprocessing to Inference and Training on Apache Spark in SK Telecom, [Spark + AI Summit 2020](https://databricks.com/session_na20/vectorized-deep-learning-acceleration-from-preprocessing-to-inference-and-training-on-apache-spark-in-sk-telecom), June 2020, ([slides](https://www.slideshare.net/databricks/vectorized-deep-learning-acceleration-from-preprocessing-to-inference-and-training-on-apache-spark-in-sk-telecom?from_action=save))
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- Running Emerging AI Applications on Big Data Platforms with Ray On Apache Spark, [Spark + AI Summit 2020](https://databricks.com/session_na20/running-emerging-ai-applications-on-big-data-platforms-with-ray-on-apache-spark), June 2020 ([slides](https://www.slideshare.net/databricks/running-emerging-ai-applications-on-big-data-platforms-with-ray-on-apache-spark))
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- Vectorized Deep Learning Acceleration from Preprocessing to Inference and Training on Apache Spark in SK Telecom, [Spark + AI Summit 2020](https://databricks.com/session_na20/vectorized-deep-learning-acceleration-from-preprocessing-to-inference-and-training-on-apache-spark-in-sk-telecom), June 2020 ([slides](https://www.slideshare.net/databricks/vectorized-deep-learning-acceleration-from-preprocessing-to-inference-and-training-on-apache-spark-in-sk-telecom?from_action=save))
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- Architecture and practice of big data analysis and deep learning model inference using Analytics Zoo on Flink, [Flink Forward Asia 2019](https://developer.aliyun.com/special/ffa2019-conference?spm=a2c6h.13239638.0.0.21f27955PCNMUB#), Nov 2019, Beijing ([slides](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/Architecture%20and%20practice%20of%20big%20data%20analysis%20and%20deep%20learning%20model%20inference%20using%20Analytics%20Zoo%20on%20Flink(FFA2019)%20.pdf))
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:caption: Real-World Application
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doc/Application/presentations.md
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doc/Application/blogs.md
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doc/Application/powered-by.md
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