Update concept-synthetic-data.md

Fixing merge conflicts

Author: ShawnJackson

articles/ai-studio/concepts/concept-synthetic-data.md

@@ -17,13 +17,15 @@ ms.custom: references_regions
 
 In Azure AI Studio, you can use synthetic data generation to efficiently produce predictions for your datasets.
 
+In Azure AI Studio, you can use synthetic data generation to efficiently produce predictions for your datasets. This article introduces you to the concept of synthetic data generation and how you can use it in machine learning.
+
 ## What is synthetic data generation?
 
 Synthetic data generation involves creating artificial data that mimics the statistical properties of real-world data. This data is generated through algorithms and machine learning techniques. You can use the data in various ways, such as computer simulations or modeling real-world events.
 
 ## Benefits
 
-In machine learning, synthetic data is particularly valuable for:
+In machine learning, synthetic data is valuable for:
 
 - **Data augmentation**: It helps in expanding the size of training datasets, which is crucial for training robust machine learning models. This expansion technique is especially useful when real-world data is scarce or expensive to obtain.
 
@@ -37,4 +39,4 @@ To see how to generate synthetic data, you can use the [sample notebook](https:/
 
 - [What is Azure AI Studio?](../what-is-ai-studio.md)
 - [Deploy Meta Llama 3.1 models with Azure AI Studio](../how-to/deploy-models-llama.md)
-- [Azure AI Studio FAQ](../faq.yml)
+- [Azure AI Studio FAQ](../faq.yml)