From 3b6c030e18484ced01d2bbe92661188bbc9f5ef0 Mon Sep 17 00:00:00 2001 From: Joerg Schad Date: Tue, 25 Feb 2020 10:34:55 +0100 Subject: [PATCH] Added APC colab notebook link. --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 4cde856..fda2906 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,7 @@ ArangoML Pipeline is a common and extensible Metadata Layer for Machine Learning Pipelines which allows Data Scientists and [DataOps](https://en.wikipedia.org/wiki/DataOps) to manage all information related to their ML pipeline in one place. **News:** -[ArangoML Pipeline Cloud](https://www.arangodb.com/2020/01/arangoml-pipeline-cloud-manage-machine-learning-metadata/) is offering a no-setup, free-to-try managed service for ArangpML Pipeline. +[ArangoML Pipeline Cloud](https://www.arangodb.com/2020/01/arangoml-pipeline-cloud-manage-machine-learning-metadata/) is offering a no-setup, free-to-try managed service for ArangpML Pipeline. A [ArangoML Pipeline Cloud tutorial](https://colab.research.google.com/github/arangoml/arangopipe/blob/master/examples/Arangopipe_with_TensorFlow_Beginner_Guide.ipynb#) is also available without any installation or Signup: ## Introduction When productizing Machine Learning Pipelines (e.g., [TensorFlow Extended](https://www.tensorflow.org/tfx/guide) or [Kubeflow](https://www.kubeflow.org/))