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* [PyTorch operator](https://github.com/kubeflow/pytorch-operator) for running PyTorch jobs
* [Seldon Core](https://github.com/kubeflow/kubeflow/tree/master/kubeflow/seldon) for running complex model deployments and non-TensorFlow serving
It’s difficult to overstate how much the community has helped bring all these projects (and more) to fruition. Just a few of the contributing companies include: Alibaba Cloud, Ant Financial, Caicloud, Canonical, Cisco, Datawire, Dell, Github, Google, Heptio, Huawei, Intel, Microsoft, Momenta, One Convergence, Pachyderm, Project Jupyter, Red Hat, Seldon, Uber and Weaveworks.
It’s difficult to overstate how much the community has helped bring all these projects (and more) to fruition. Just a few of the contributing companies include: Alibaba Cloud, Ant Financial, Caicloud, Canonical, Cisco, Datawire, Dell, GitHub, Google, Heptio, Huawei, Intel, Microsoft, Momenta, One Convergence, Pachyderm, Project Jupyter, Red Hat, Seldon, Uber and Weaveworks.
# Learning More
If you’d like to try out Kubeflow, we have a number of options for you:
1. You can use sample walkthroughs hosted on [Katacoda](https://www.katacoda.com/kubeflow)
2. You can follow a guided tutorial with existing models from the [examples repository](https://github.com/kubeflow/examples). These include the [Github Issue Summarization](https://github.com/kubeflow/examples/tree/master/github_issue_summarization), [MNIST](https://github.com/kubeflow/examples/tree/master/mnist) and [Reinforcement Learning with Agents](https://github.com/kubeflow/examples/tree/master/agents).
2. You can follow a guided tutorial with existing models from the [examples repository](https://github.com/kubeflow/examples). These include the [GitHub Issue Summarization](https://github.com/kubeflow/examples/tree/master/github_issue_summarization), [MNIST](https://github.com/kubeflow/examples/tree/master/mnist) and [Reinforcement Learning with Agents](https://github.com/kubeflow/examples/tree/master/agents).
3. You can start a cluster on your own and try your own model. Any Kubernetes conformant cluster will support Kubeflow including those from contributors [Caicloud](https://www.prnewswire.com/news-releases/caicloud-releases-its-kubernetes-based-cluster-as-a-service-product-claas-20-and-the-first-tensorflow-as-a-service-taas-11-while-closing-6m-series-a-funding-300418071.html), [Canonical](https://jujucharms.com/canonical-kubernetes/), [Google](https://cloud.google.com/kubernetes-engine/docs/how-to/creating-a-container-cluster), [Heptio](https://heptio.com/products/kubernetes-subscription/), [Mesosphere](https://github.com/mesosphere/dcos-kubernetes-quickstart), [Microsoft](https://docs.microsoft.com/en-us/azure/aks/kubernetes-walkthrough), [IBM](https://cloud.ibm.com/docs/containers?topic=containers-cs_cluster_tutorial#cs_cluster_tutorial), [Red Hat/Openshift ](https://docs.openshift.com/container-platform/3.3/install_config/install/quick_install.html#install-config-install-quick-install)and [Weaveworks](https://www.weave.works/product/cloud/).
There were also a number of sessions at KubeCon + CloudNativeCon EU 2018 covering Kubeflow. The links to the talks are here; the associated videos will be posted in the coming days.