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docs: add Alibaba Cloud presentations from KubeCon China (#13689)
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Signed-off-by: shuangkun <[email protected]>
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shuangkun authored Oct 2, 2024
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2 changes: 2 additions & 0 deletions README.md
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* [Distributed Machine Learning Patterns from Manning Publication](https://github.com/terrytangyuan/distributed-ml-patterns)
* [Engineering Cloud Native AI Platform](https://github.com/terrytangyuan/public-talks/tree/main/talks/platform-con-2024-engineering-cloud-native-ai-platform)
* [Managing Thousands of Automatic Machine Learning Experiments with Argo and Katib](https://github.com/terrytangyuan/public-talks/blob/main/talks/argocon-automl-experiments-2022)
* [Revolutionizing Scientific Simulations with Argo Workflows](https://www.youtube.com/watch?v=BYVf7GhfiRg)
* [Running Argo Workflows Across Multiple Kubernetes Clusters](https://admiralty.io/blog/running-argo-workflows-across-multiple-kubernetes-clusters/)
* [Scaling Kubernetes: Best Practices for Managing Large-Scale Batch Jobs with Spark and Argo Workflow](https://www.youtube.com/watch?v=KqEKRPjy4aE)
* [Open Source Model Management Roundup: Polyaxon, Argo, and Seldon](https://www.anaconda.com/blog/developer-blog/open-source-model-management-roundup-polyaxon-argo-and-seldon/)
* [Producing 200 OpenStreetMap extracts in 35 minutes using a scalable data workflow](https://www.interline.io/blog/scaling-openstreetmap-data-workflows/)
* [Production-Ready AI Platform on Kubernetes](https://github.com/terrytangyuan/public-talks/tree/main/talks/kubecon-europe-2024-production-ai-platform-on-k8s)
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2 changes: 2 additions & 0 deletions docs/README.md
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* [Distributed Machine Learning Patterns from Manning Publication](https://github.com/terrytangyuan/distributed-ml-patterns)
* [Engineering Cloud Native AI Platform](https://github.com/terrytangyuan/public-talks/tree/main/talks/platform-con-2024-engineering-cloud-native-ai-platform)
* [Managing Thousands of Automatic Machine Learning Experiments with Argo and Katib](https://github.com/terrytangyuan/public-talks/blob/main/talks/argocon-automl-experiments-2022)
* [Revolutionizing Scientific Simulations with Argo Workflows](https://www.youtube.com/watch?v=BYVf7GhfiRg)
* [Running Argo Workflows Across Multiple Kubernetes Clusters](https://admiralty.io/blog/running-argo-workflows-across-multiple-kubernetes-clusters/)
* [Scaling Kubernetes: Best Practices for Managing Large-Scale Batch Jobs with Spark and Argo Workflow](https://www.youtube.com/watch?v=KqEKRPjy4aE)
* [Open Source Model Management Roundup: Polyaxon, Argo, and Seldon](https://www.anaconda.com/blog/developer-blog/open-source-model-management-roundup-polyaxon-argo-and-seldon/)
* [Producing 200 OpenStreetMap extracts in 35 minutes using a scalable data workflow](https://www.interline.io/blog/scaling-openstreetmap-data-workflows/)
* [Production-Ready AI Platform on Kubernetes](https://github.com/terrytangyuan/public-talks/tree/main/talks/kubecon-europe-2024-production-ai-platform-on-k8s)
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## Videos

* [Running a Data Replication Pipeline on Kubernetes with Argo and Singer.io](https://towardsdatascience.com/running-a-data-replication-pipeline-on-kubernetes-with-argo-and-singer-io-2fab5b0bad?utm_source=argo-docs)
* [Scaling Kubernetes: Best Practices for Managing Large-Scale Batch Jobs with Spark and Argo Workflow](https://www.youtube.com/watch?v=KqEKRPjy4aE)

## Books

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* [Managing Thousands of Automatic Machine Learning Experiments with Argo and Katib](https://github.com/terrytangyuan/public-talks/blob/main/talks/argocon-automl-experiments-2022)
* [MLOps at TripAdvisor: ML Models CI/CD Automation with Argo - Ang Gao (Principal Software Engineer, TripAdvisor)](https://www.youtube.com/watch?v=BochC4GKxbo&list=PLGHfqDpnXFXK4E8XzasScagiJk-8BPgva&index=2&utm_source=argo-docs)
* [Production-Ready AI Platform on Kubernetes](https://github.com/terrytangyuan/public-talks/tree/main/talks/kubecon-europe-2024-production-ai-platform-on-k8s)
* [Revolutionizing Scientific Simulations with Argo Workflows](https://www.youtube.com/watch?v=BYVf7GhfiRg)
* [Towards Cloud-Native Distributed Machine Learning Pipelines at Scale](https://github.com/terrytangyuan/public-talks/tree/main/talks/towards-cloud-native-distributed-machine-learning-pipelines-at-scale-pydata-global-2021)

## Books
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