Update powered-by.md
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Jason Dai
GitHub
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* __Alibaba__
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<br>[Deploy Analytics Zoo in Aliyun EMR](https://partners-intl.aliyun.com/help/doc-detail/93155.htm)
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<br>[Better Together: Privacy-Preserving Machine Learning](https://www.intel.com/content/www/us/en/artificial-intelligence/posts/alibaba-privacy-preserving-machine-learning.html)
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<br>• [Deploy Analytics Zoo in Aliyun EMR](https://partners-intl.aliyun.com/help/doc-detail/93155.htm)
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<br>• [Better Together: Privacy-Preserving Machine Learning](https://www.intel.com/content/www/us/en/artificial-intelligence/posts/alibaba-privacy-preserving-machine-learning.html)
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* __Baosight__
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<br>[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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<br>• [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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* __BBVA__
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<br>[A Graph Convolutional Network Implementation](https://emartinezs44.medium.com/graph-convolutions-networks-ad8295b3ce57)
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<br>• [A Graph Convolutional Network Implementation](https://emartinezs44.medium.com/graph-convolutions-networks-ad8295b3ce57)
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* __Burger King__
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<br>[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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<br>[How Intel and Burger King built an order recommendation system that preserves customer privacy](https://venturebeat.com/2021/04/06/how-intel-and-burger-king-built-an-order-recommendation-system-that-preserves-customer-privacy/)
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<br>[Burger King: Context-Aware Recommendations (video)](https://www.intel.com/content/www/us/en/customer-spotlight/stories/burger-king-ai-customer-story.html)
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<br>• [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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<br>• [How Intel and Burger King built an order recommendation system that preserves customer privacy](https://venturebeat.com/2021/04/06/how-intel-and-burger-king-built-an-order-recommendation-system-that-preserves-customer-privacy/)
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<br>• [Burger King: Context-Aware Recommendations (video)](https://www.intel.com/content/www/us/en/customer-spotlight/stories/burger-king-ai-customer-story.html)
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* __Capgemini__
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<br>[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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<br>• [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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* __CERN__
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<br>[Deep Learning Pipelines for High Energy Physics using Apache Spark with Distributed Keras on Analytics Zoo](https://databricks.com/session_eu19/deep-learning-pipelines-for-high-energy-physics-using-apache-spark-with-distributed-keras-on-analytics-zoo)
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<br>[Topology classification at CERN's Large Hadron Collider using 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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<br>[Deep Learning on Apache Spark at CERN's Large Hadron Collider with Intel Technologies](https://databricks.com/session/deep-learning-on-apache-spark-at-cerns-large-hadron-collider-with-intel-technologies)
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<br>• [Deep Learning Pipelines for High Energy Physics using Apache Spark with Distributed Keras on Analytics Zoo](https://databricks.com/session_eu19/deep-learning-pipelines-for-high-energy-physics-using-apache-spark-with-distributed-keras-on-analytics-zoo)
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<br>• [Topology classification at CERN's Large Hadron Collider using 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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<br>• [Deep Learning on Apache Spark at CERN's Large Hadron Collider with Intel Technologies](https://databricks.com/session/deep-learning-on-apache-spark-at-cerns-large-hadron-collider-with-intel-technologies)
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* __China Telecom__
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<br>[Face Recognition Application and Practice Based on Intel Analytics Zoo: Part 1](https://mp.weixin.qq.com/s/FEiXoTDi-yy04PJ2Mlfl4A) (in Chinese)
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<br>[Face Recognition Application and Practice Based on Intel Analytics Zoo: Part 2](https://mp.weixin.qq.com/s/VIyWRORTAVAAsC4v6Fi0xw) (in Chinese)
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<br>• [Face Recognition Application and Practice Based on Intel Analytics Zoo: Part 1](https://mp.weixin.qq.com/s/FEiXoTDi-yy04PJ2Mlfl4A) (in Chinese)
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<br>• [Face Recognition Application and Practice Based on Intel Analytics Zoo: Part 2](https://mp.weixin.qq.com/s/VIyWRORTAVAAsC4v6Fi0xw) (in Chinese)
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* __Cray__
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<br>[A deep learning approach for precipitation nowcasting with RNN using Analytics Zoo in Cray](https://conferences.oreilly.com/strata/strata-ny-2018/public/schedule/detail/69413)
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<br>• [A deep learning approach for precipitation nowcasting with RNN using Analytics Zoo in Cray](https://conferences.oreilly.com/strata/strata-ny-2018/public/schedule/detail/69413)
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* __Dell EMC__
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<br>[Build AI on PowerEdge with Domino Data Labs, Apache Spark and Analytics Zoo](https://community.emc.com/community/products/rs_for_ai/blog/2019/09/19/build-ai-on-poweredge-with-domino-data-labs-and-apache-spark)
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<br>[AI-assisted Radiology Using Distributed Deep
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<br>• [Build AI on PowerEdge with Domino Data Labs, Apache Spark and Analytics Zoo](https://community.emc.com/community/products/rs_for_ai/blog/2019/09/19/build-ai-on-poweredge-with-domino-data-labs-and-apache-spark)
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<br>• [AI-assisted Radiology Using Distributed Deep
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Learning on Apache Spark and Analytics Zoo](https://www.dellemc.com/resources/en-us/asset/white-papers/solutions/h17686_hornet_wp.pdf)
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<br>[Using Deep Learning on Apache Spark to Diagnose Thoracic Pathology from Chest X-rays](https://databricks.com/session/using-deep-learning-on-apache-spark-to-diagnose-thoracic-pathology-from-chest-x-rays)
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<br>• [Using Deep Learning on Apache Spark to Diagnose Thoracic Pathology from Chest X-rays](https://databricks.com/session/using-deep-learning-on-apache-spark-to-diagnose-thoracic-pathology-from-chest-x-rays)
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* __GoldWind__
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<br>[Intel big data analysis + AI platform helps GoldWind to build a new energy intelligent power prediction solution](https://www.intel.cn/content/www/cn/zh/analytics/artificial-intelligence/create-power-forecasting-solutions.html)
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<br>• [Intel big data analysis + AI platform helps GoldWind to build a new energy intelligent power prediction solution](https://www.intel.cn/content/www/cn/zh/analytics/artificial-intelligence/create-power-forecasting-solutions.html)
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* __Inspur__
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<br>[Inspur E2E Smart Transportation CV application](https://jason-dai.github.io/cvpr2021/slides/Inspur%20E2E%20Smart%20Transportation%20CV%20application%20-CVPR21.pdf)
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<br>[Inspur End-to-End Smart Computing Solution with Intel Analytics Zoo](https://dpgresources.intel.com/asset-library/inspur-end-to-end-smart-computing-solution-with-intel-analytics-zoo/)
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<br>• [Inspur E2E Smart Transportation CV application](https://jason-dai.github.io/cvpr2021/slides/Inspur%20E2E%20Smart%20Transportation%20CV%20application%20-CVPR21.pdf)
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<br>• [Inspur End-to-End Smart Computing Solution with Intel Analytics Zoo](https://dpgresources.intel.com/asset-library/inspur-end-to-end-smart-computing-solution-with-intel-analytics-zoo/)
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* __JD__
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<br>[Object Detection and Image Feature Extraction at JD.com](https://software.intel.com/en-us/articles/building-large-scale-image-feature-extraction-with-bigdl-at-jdcom)
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<br>• [Object Detection and Image Feature Extraction at JD.com](https://software.intel.com/en-us/articles/building-large-scale-image-feature-extraction-with-bigdl-at-jdcom)
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* __MasterCard__
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<br>["AI at Scale" in Mastercard with BigDL](https://www.intel.com/content/www/us/en/developer/articles/technical/ai-at-scale-in-mastercard-with-bigdl0.html)
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<br>[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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<br>• ["AI at Scale" in Mastercard with BigDL](https://www.intel.com/content/www/us/en/developer/articles/technical/ai-at-scale-in-mastercard-with-bigdl0.html)
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<br>• [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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* __Microsoft Azure__
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<br>[Use Analytics Zoo to Inject AI Into Customer Service Platforms on Microsoft Azure: Part 1](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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<br>[Use Analytics Zoo to Inject AI Into Customer Service Platforms on Microsoft Azure: Part 2](https://www.infoq.com/articles/analytics-zoo-qa-module/?from=timeline&isappinstalled=0)
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<br>• [Use Analytics Zoo to Inject AI Into Customer Service Platforms on Microsoft Azure: Part 1](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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<br>• [Use Analytics Zoo to Inject AI Into Customer Service Platforms on Microsoft Azure: Part 2](https://www.infoq.com/articles/analytics-zoo-qa-module/?from=timeline&isappinstalled=0)
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* __Midea__
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<br>[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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<br>[Ability to add "eyes" and "brains" to smart manufacturing](https://www.intel.cn/content/www/cn/zh/analytics/artificial-intelligence/midea-case-study.html) (in Chinese)
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<br>• [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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<br>• [Ability to add "eyes" and "brains" to smart manufacturing](https://www.intel.cn/content/www/cn/zh/analytics/artificial-intelligence/midea-case-study.html) (in Chinese)
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* __MLSListings__
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<br>[Image Similarity-Based House Recommendations and Search](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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<br>• [Image Similarity-Based House Recommendations and Search](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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* __NeuSoft/BMW__
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<br>[Neusoft RealSight APM partners with Intel to create an application performance management platform with active defense capabilities](https://platform.neusoft.com/2020/01/17/xw-intel.html) (in Chinese)
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<br>• [Neusoft RealSight APM partners with Intel to create an application performance management platform with active defense capabilities](https://platform.neusoft.com/2020/01/17/xw-intel.html) (in Chinese)
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* __NeuSoft/Mazda__
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<br>[JD, Neusoft and Intel Jointly Building Intelligent and Connected Vehicle Cloud for HaiMa(former Hainan Mazda)](https://www.neusoft.com/Products/Platforms/2472/4735110231.html)
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<br>[JD, Neusoft and Intel Jointly Building Intelligent and Connected Vehicle Cloud for Hainan-Mazda](https://platform.neusoft.com/2020/06/11/jjfa-haimaqiche.html) (in Chinese)
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<br>• [JD, Neusoft and Intel Jointly Building Intelligent and Connected Vehicle Cloud for HaiMa(former Hainan Mazda)](https://www.neusoft.com/Products/Platforms/2472/4735110231.html)
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<br>• [JD, Neusoft and Intel Jointly Building Intelligent and Connected Vehicle Cloud for Hainan-Mazda](https://platform.neusoft.com/2020/06/11/jjfa-haimaqiche.html) (in Chinese)
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* __Office Depot__
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<br>[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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<br>[Office Depot product recommender using Analytics Zoo on AWS](https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/73079)
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<br>• [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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<br>• [Office Depot product recommender using Analytics Zoo on AWS](https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/73079)
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* __SK Telecom__
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<br>[White Paper: Reference Architecture for Confidential Computing on SKT 5G MEC](https://github.com/analytics-zoo/analytics-zoo.github.io/blob/master/presentations/reference-architecture-for-confidential-computing-on-skt-5g-mec-1635323587.pdf)
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<br>[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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<br>[Vectorized Deep Learning Acceleration from Preprocessing to Inference and Training on Apache Spark in SK Telecom](https://databricks.com/session_na20/vectorized-deep-learning-acceleration-from-preprocessing-to-inference-and-training-on-apache-spark-in-sk-telecom)
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<br>[Apache Spark AI Use Case in Telco: Network Quality Analysis and Prediction with Geospatial Visualization](https://databricks.com/session_eu19/apache-spark-ai-use-case-in-telco-network-quality-analysis-and-prediction-with-geospatial-visualization)
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<br>• [Reference Architecture for Confidential Computing on SKT 5G MEC](https://networkbuilders.intel.com/solutionslibrary/reference-architecture-for-confidential-computing-on-skt-5g-mec)
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<br>• [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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<br>• [Vectorized Deep Learning Acceleration from Preprocessing to Inference and Training on Apache Spark in SK Telecom](https://databricks.com/session_na20/vectorized-deep-learning-acceleration-from-preprocessing-to-inference-and-training-on-apache-spark-in-sk-telecom)
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<br>• [Apache Spark AI Use Case in Telco: Network Quality Analysis and Prediction with Geospatial Visualization](https://databricks.com/session_eu19/apache-spark-ai-use-case-in-telco-network-quality-analysis-and-prediction-with-geospatial-visualization)
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* __Talroo__
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<br>[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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<br>[Job recommendations leveraging deep learning using Analytics Zoo on Apache Spark and BigDL](https://conferences.oreilly.com/strata/strata-ny-2018/public/schedule/detail/69113)
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<br>• [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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<br>• [Job recommendations leveraging deep learning using Analytics Zoo on Apache Spark and BigDL](https://conferences.oreilly.com/strata/strata-ny-2018/public/schedule/detail/69113)
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* __Telefonica__
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<br>[Running Analytics Zoo jobs on Telefónica Open Cloud’s MRS Service](https://medium.com/@fernando.delaiglesia/running-analytics-zoo-jobs-on-telef%C3%B3nica-open-clouds-mrs-service-2e64bc823c50)
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<br>• [Running Analytics Zoo jobs on Telefónica Open Cloud’s MRS Service](https://medium.com/@fernando.delaiglesia/running-analytics-zoo-jobs-on-telef%C3%B3nica-open-clouds-mrs-service-2e64bc823c50)
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* __Tencent__
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<br>[Analytics Zoo helps Tencent Cloud improve the performance of its intelligent titanium machine learning platform](https://www.intel.cn/content/www/cn/zh/service-providers/analytics-zoo-helps-tencent-cloud-improve-ti-ml-platform-performance.html)
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<br>[Tencent* Cloud Leverages Analytics Zoo to Improve Performance of TI-ONE* ML Platform](https://software.intel.com/content/www/us/en/develop/articles/tencent-cloud-leverages-analytics-zoo-to-improve-performance-of-ti-one-ml-platform.html)
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<br>[Enhance Tencent's TUSI Identity Practice with Intel Analytics Zoo](https://mp.weixin.qq.com/s?__biz=MzAwNzc5NzM5Mw==&mid=2651030944&idx=1&sn=d6e06c6e14a7355971953a501689b232&chksm=808f8a5eb7f80348fc8e88c4c9e415341bf43ef6bdf3fd4f3001da89e2c9ba7fa2ed5deeb09a&mpshare=1&scene=1&srcid=0412WxM3eWdsLLoO2TYJGWbS&pass_ticket=E6l%2FfOZNKjhr05lsU7inAVCi7mAy5LFEehvEJOS2ZGdHg6%2FH%2BeBQisHA9sfXDOoy#rd) (in Chinese)
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<br>• [Analytics Zoo helps Tencent Cloud improve the performance of its intelligent titanium machine learning platform](https://www.intel.cn/content/www/cn/zh/service-providers/analytics-zoo-helps-tencent-cloud-improve-ti-ml-platform-performance.html)
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<br>• [Tencent Cloud Leverages Analytics Zoo to Improve Performance of TI-ONE ML Platform](https://software.intel.com/content/www/us/en/develop/articles/tencent-cloud-leverages-analytics-zoo-to-improve-performance-of-ti-one-ml-platform.html)
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<br>• [Enhance Tencent's TUSI Identity Practice with Intel Analytics Zoo](https://mp.weixin.qq.com/s?__biz=MzAwNzc5NzM5Mw==&mid=2651030944&idx=1&sn=d6e06c6e14a7355971953a501689b232&chksm=808f8a5eb7f80348fc8e88c4c9e415341bf43ef6bdf3fd4f3001da89e2c9ba7fa2ed5deeb09a&mpshare=1&scene=1&srcid=0412WxM3eWdsLLoO2TYJGWbS&pass_ticket=E6l%2FfOZNKjhr05lsU7inAVCi7mAy5LFEehvEJOS2ZGdHg6%2FH%2BeBQisHA9sfXDOoy#rd) (in Chinese)
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* __UC Berkeley RISELab__
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<br>[RayOnSpark: Running Emerging AI Applications on Big Data Clusters with Ray and 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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<br>[Scalable AutoML for Time Series Prediction Using Ray and Analytics Zoo](https://medium.com/riselab/scalable-automl-for-time-series-prediction-using-ray-and-analytics-zoo-b79a6fd08139)
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<br>• [RayOnSpark: Running Emerging AI Applications on Big Data Clusters with Ray and 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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<br>• [Scalable AutoML for Time Series Prediction Using Ray and Analytics Zoo](https://medium.com/riselab/scalable-automl-for-time-series-prediction-using-ray-and-analytics-zoo-b79a6fd08139)
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* __UnionPay__
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<br>[Technical Verification of SGX and BigDL Based Privacy Computing for Multi Source Financial Big Data](https://www.intel.cn/content/www/cn/zh/now/data-centric/sgx-bigdl-financial-big-data.html) (in Chinese)
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<br>• [Technical Verification of SGX and BigDL Based Privacy Computing for Multi Source Financial Big Data](https://www.intel.cn/content/www/cn/zh/now/data-centric/sgx-bigdl-financial-big-data.html) (in Chinese)
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* __World Bank__
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<br>[Using Crowdsourced Images to Create Image Recognition Models with Analytics Zoo using BigDL](https://databricks.com/session/using-crowdsourced-images-to-create-image-recognition-models-with-bigdl)
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<br>• [Using Crowdsourced Images to Create Image Recognition Models with Analytics Zoo using BigDL](https://databricks.com/session/using-crowdsourced-images-to-create-image-recognition-models-with-bigdl)
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* __Yunda__
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<br>[Intelligent transformation brings "quality change" to the express delivery industry](https://www.intel.cn/content/www/cn/zh/analytics/artificial-intelligence/yunda-brings-quality-change-to-the-express-delivery-industry.html) (in Chinese)
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<br>• [Intelligent transformation brings "quality change" to the express delivery industry](https://www.intel.cn/content/www/cn/zh/analytics/artificial-intelligence/yunda-brings-quality-change-to-the-express-delivery-industry.html) (in Chinese)
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