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Revert 756 #798

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Oct 31, 2022
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Revert 756 #798

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a4a782e
Revert "Refine example notebooks (#756)"
blrchen Oct 31, 2022
f50e332
Resolve conflict
blrchen Oct 31, 2022
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6 changes: 3 additions & 3 deletions docs/dev_guide/new_contributor_guide.md
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Expand Up @@ -6,19 +6,19 @@ parent: Feathr Developer Guides

# What can I contribute?
All forms of contributions are welcome, including and not limited to:
* Improve or contribute new [notebook samples](https://github.com/feathr-ai/feathr/tree/main/docs/samples)
* Improve or contribute new [notebook samples](https://github.com/feathr-ai/feathr/tree/main/feathr_project/feathrcli/data/feathr_user_workspace)
* Add tutorial, blog posts, tech talks etc
* Increase media coverage and exposure
* Improve user-facing documentation or developer-facing documentation
* Add testing code
* Add testing code
* Add new features
* Refactor and improve architecture
* For any other forms of contribution and collaboration, don't hesitate to reach out to us.

# I am interested, how can I start?
If you are new to this project, we recommend start with [`good-first-issue`](https://github.com/feathr-ai/feathr/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22).

The issues are also labled with what types of programming language the task need.
The issues are also labled with what types of programming language the task need.
* [`good-first-issue` and `Python`](https://github.com/feathr-ai/feathr/issues?q=is%3Aopen+label%3A%22good+first+issue%22+label%3Apython)
* [`good-first-issue` and `Scala`](https://github.com/feathr-ai/feathr/issues?q=is%3Aopen+label%3A%22good+first+issue%22+label%3Ascala)
* [`good-first-issue` and `Java`](https://github.com/feathr-ai/feathr/issues?q=is%3Aopen+label%3A%22good+first+issue%22+label%3Ajava)
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6 changes: 3 additions & 3 deletions docs/quickstart_databricks.md
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Expand Up @@ -5,13 +5,13 @@ title: Quick Start Guide with Databricks

# Feathr Quick Start Guide with Databricks

For Databricks, you can simply upload [this notebook](./samples/databricks/databricks_quickstart_nyc_taxi_demo.ipynb) to your Databricks cluster and just run it in the Databricks cluster. It has been pre-configured to use the current Databricks cluster to submit jobs.
For Databricks, you can simply upload [this notebook](./samples/databricks/databricks_quickstart_nyc_taxi_driver.ipynb) to your Databricks cluster and just run it in the Databricks cluster. It has been pre-configured to use the current Databricks cluster to submit jobs.

1. Import Notebooks in your Databricks cluster:

![Import Notebooks](./images/databricks_quickstart1.png)

2. Paste the [link to Databricks getting started notebook](./samples/databricks/databricks_quickstart_nyc_taxi_demo.ipynb):
2. Paste the [link to Databricks getting started notebook](./samples/databricks/databricks_quickstart_nyc_taxi_driver.ipynb):

![Import Notebooks](./images/databricks_quickstart2.png)

Expand All @@ -21,7 +21,7 @@ For Databricks, you can simply upload [this notebook](./samples/databricks/datab

Although Databricks Notebooks are great tools, there are also large developer communities that prefer the usage of Visual Studio Code, where [it has native support for Python and Jupyter Notebooks](https://code.visualstudio.com/docs/datascience/jupyter-notebooks) with many great features such as syntax highlight and IntelliSense.

In [this notebook](./samples/databricks/databricks_quickstart_nyc_taxi_demo.ipynb), there are a few lines of code like this:
In [this notebook](./samples/databricks/databricks_quickstart_nyc_taxi_driver.ipynb), there are a few lines of code like this:

```python
# Get current databricks notebook context
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2 changes: 1 addition & 1 deletion docs/quickstart_synapse.md
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Expand Up @@ -24,7 +24,7 @@ Feathr has native cloud integration. Here are the steps to use Feathr on Azure:

1. Follow the [Feathr ARM deployment guide](https://feathr-ai.github.io/feathr/how-to-guides/azure-deployment-arm.html) to run Feathr on Azure. This allows you to quickly get started with automated deployment using Azure Resource Manager template. Alternatively, if you want to set up everything manually, you can checkout the [Feathr CLI deployment guide](https://feathr-ai.github.io/feathr/how-to-guides/azure-deployment-cli.html) to run Feathr on Azure. This allows you to understand what is going on and set up one resource at a time.

2. Once the deployment is complete,run the Feathr Jupyter Notebook by clicking this button: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/feathr-ai/feathr/main?labpath=docs%2Fsamples%2Fnyc_taxi_demo.ipynb).
2. Once the deployment is complete,run the Feathr Jupyter Notebook by clicking this button: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/feathr-ai/feathr/main?labpath=feathr_project%2Ffeathrcli%2Fdata%2Ffeathr_user_workspace%2Fnyc_driver_demo.ipynb).
3. You only need to change the specified `Resource Prefix`.

## Step 2: Install Feathr
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