diff --git a/5-Data-Science-In-Cloud/README.md b/5-Data-Science-In-Cloud/README.md index e7f28ab..227cc10 100644 --- a/5-Data-Science-In-Cloud/README.md +++ b/5-Data-Science-In-Cloud/README.md @@ -1,5 +1,7 @@ # Data Science in the Cloud +![cloud-picture](img/cloud-picture.jpg) + When it comes to doing data science with big data, the cloud can be a game changer. In the next three lessons, we are going to see what the cloud is and why it can be very helpful. We are also going to explore a heart failure dataset and build a model to help assess the probability of someone having a heart failure. We will use the power of the cloud to train, deploy and consume a model in two different ways. One way using only the user interface in a Low code/No code fashion, the other way using the Azure Machine Learning Software Developer Kit (Azure ML SDK). ![project-schema](19-tbd/img/project-schema.PNG) diff --git a/5-Data-Science-In-Cloud/img/cloud-picture.jpg b/5-Data-Science-In-Cloud/img/cloud-picture.jpg new file mode 100644 index 0000000..3a7de57 Binary files /dev/null and b/5-Data-Science-In-Cloud/img/cloud-picture.jpg differ