Merge pull request #3 from databricks-industry-solutions/Fix-linked-z…

…ingg-version

Update 00_Intro_&_Config.py

00_Intro_&_Config.py

@@ -1,5 +1,5 @@
 # Databricks notebook source
-# MAGIC %md The purpose of this notebook is to introduce the Zingg Product Matching with Image Data solution accelerator and provide access to the configuration settings used across the various notebooks in the accelerator.  This notebook was developed using a **Databricks 12.2 LTS** cluster.
+# MAGIC %md The purpose of this notebook is to introduce the Zingg Product Matching with Image Data solution accelerator and provide access to the configuration settings used across the various notebooks in the accelerator.  These notebooks will require a **Databricks 14.2** cluster to be compatible with zingg 0.4.0.
 
 # COMMAND ----------
 
@@ -34,7 +34,7 @@
 
 # MAGIC %md ##Installation & Verification
 # MAGIC
-# MAGIC Zingg with support for array-comparisons (which is the basis for our image comparisons) will be supported in the 0.4 version of the product.  At the time of development, this version was available as a preview which can be accessed [here](https://github.com/zinggAI/zingg/releases/tag/0.4.0_ARRAY).
+# MAGIC Zingg with support for array-comparisons (which is the basis for our image comparisons) are supported in the 0.4.0 version of the product, which can be accessed [here](https://github.com/zinggAI/zingg/releases/tag/v0.4.0).
 # MAGIC
 # MAGIC To enable Zingg support, you will need to install the JAR file within your Databricks cluster as a [workspace library](https://docs.databricks.com/libraries/workspace-libraries.html).  In addition, you will need to install the corresponding WHL file, as either a workspace or a notebook-scoped library.  For simplicity, it's recommended you install the WHL, also available [here](https://github.com/zinggAI/zingg/releases/tag/0.4.0_ARRAY), as a workspace library.
 # MAGIC