Add README for examples folder (zenml-io#1860)

* draft README file

* update with templates info

* updated following PR comments

* reorder table

examples/README.md

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+# ZenML Use Cases
+
+This folder contains examples of ZenML pipelines. These are more involved use
+cases with production-ready pipelines, with the exception of
+some that will be indicated in the table below.
+
+These core demonstrations of ZenML showcase the power of the framework in real
+scenarios that use cloud infrastructure or other cloud components.
+Explanations for how to use and run the use cases can be found in the README
+associated with each sub-folder.
+
+{% hint style="info" %}
+This directory previously contained examples of ZenML integrations and how to
+use them. These have been ingested into the core library as integration tests.
+It is therefore still possible to view the code at
+[`/tests/integration/examples`](https://github.com/zenml-io/zenml/tree/main/tests/integration/examples)
+but for explanations on how to use them, please refer to our dedicated [Component
+guide](https://docs.zenml.io/stacks-and-components/component-guide) in our
+documentation which has been updated with all the latest information.
+{% endhint %}
+
+Note that our full use cases are all implemented as templates so you can start
+with our code and then adapt the specifics to your individual needs. To learn
+more about how to do this, please [visit our dedicated documentation
+page](https://docs.zenml.io/user-guide/starter-guide/using-project-templates) on
+this.
+
+| Name | Description | Integrations | Core Project |
+| ---- | ----------- | ------------ | ------------ |
+| quickstart | This is our quickstart example showcasing basic functionality and a workflow to get you started with the ZenML framework | mlflow | ✅ |
+| e2e | Trains one or more scikit-learn classification models to make predictions on tabular classification datasets | scikit-learn | ✅ |
+| generative_chat | LEGACY: constructs a vector store to be used by a LLM-based chatbot based on documentation and data from a variety of sources | langchain, llama-index, slack |   |
+| label_studio_annotation | LEGACY: shows how to use the Label Studio integration for annotation in a computer-vision use case and series of pipelines | label_studio, pillow |   |
+| label_studio_text_annotation | LEGACY: shows how to use the Label Studio integration in a NLP / text-based use case and series of pipelines | label_studio |   |
+
+## ❓ Questions / Further Assistance
+
+If you have any questions about how to get going with these use cases, or if
+you're wondering how you can adapt them to your particular needs, please do
+[reach out to us on Slack](https://zenml.io/slack-invite/)!