Fix acrolynx scores

Author: mhamilton723

articles/synapse-analytics/machine-learning/synapse-machine-learning-library.md

@@ -13,7 +13,7 @@ ms.author: sngun
 
 SynapseML (previously known as MMLSpark), is an open-source library that simplifies the creation of massively scalable machine learning (ML) pipelines. SynapseML provides simple, composable, and distributed APIs for a wide variety of different machine learning tasks such as text analytics, vision, anomaly detection, and many others. SynapseML is built on the [Apache Spark distributed computing framework](https://spark.apache.org/) and shares the same API as the [SparkML/MLLib library](https://spark.apache.org/mllib/), allowing you to seamlessly embed SynapseML models into existing Apache Spark workflows.
 
-With SynapseML, you can build scalable and intelligent systems to solve challenges in domains such as anomaly detection, computer vision, deep learning, text analytics, and others. SynapseML can train and evaluate models on single-node, multi-node, and elastically resizable clusters of computers, so you can scale your work without wasting resources. SynapseML is usable across Python, R, Scala, Java, and .NET. Furthermore, its API abstracts over a wide variety of databases, file systems, and cloud data stores to simplify experiments no matter where data is located.
+With SynapseML, you can build scalable and intelligent systems to solve challenges in domains such as anomaly detection, computer vision, deep learning, text analytics, and others. SynapseML can train and evaluate models on single-node, multi-node, and elastically resizable clusters of computers. This lets you scale your work without wasting resources. SynapseML is usable across Python, R, Scala, Java, and .NET. Furthermore, its API abstracts over a wide variety of databases, file systems, and cloud data stores to simplify experiments no matter where data is located.
 
 SynapseML requires Scala 2.12, Spark 3.0+, and Python 3.6+.
 
@@ -24,14 +24,14 @@ SynapseML requires Scala 2.12, Spark 3.0+, and Python 3.6+.
 
 SynapseML offers a unified API that simplifies developing fault-tolerant distributed programs. In particular, SynapseML exposes many different machine learning frameworks under a single API that is scalable, data and language agnostic, and works for batch, streaming, and serving applications.
 
-A unified API standardizes many tools, frameworks, algorithms and streamlines the distributed machine learning experience. It enables developers to quickly compose disparate machine learning frameworks, keeps code clean, and enables workflows that require more than one framework, such as web-supervised learning, search engine creation, and many others. 
+A unified API standardizes many tools, frameworks, algorithms and streamlines the distributed machine learning experience. It enables developers to quickly compose disparate machine learning frameworks, keeps code clean, and enables workflows that require more than one framework. For example, workflows such as web-supervised learning or search-engine creation require multiple services and frameworks. SynapseML shields users from this extra complexity.
 
 
 ### Use pre-built intelligent models
 
-Many tools in SynapseML don't require a large labeled training dataset. Instead, SynapseML provides simple APIs for pre-built intelligent services, such as Azure Cognitive Services, to quickly solve large-scale AI challenges related to both business and research. SynapseML enables developers to embed over 50 different state-of-the-art ML services directly into their systems and databases. These ready-to-use algorithms can parse a wide variety of documents, transcribe multi-speaker conversations in real time, and translate text to over 100 different languages. For more examples of how to use pre-built AI to solve tasks quicklyt, see [the SynapseML cognitive service examples](https://microsoft.github.io/SynapseML/docs/features/cognitive_services/CognitiveServices%20-%20Overview/).
+Many tools in SynapseML don't require a large labeled training dataset. Instead, SynapseML provides simple APIs for pre-built intelligent services, such as Azure Cognitive Services, to quickly solve large-scale AI challenges related to both business and research. SynapseML enables developers to embed over 50 different state-of-the-art ML services directly into their systems and databases. These ready-to-use algorithms can parse a wide variety of documents, transcribe multi-speaker conversations in real time, and translate text to over 100 different languages. For more examples of how to use pre-built AI to solve tasks quickly, see [the SynapseML cognitive service examples](https://microsoft.github.io/SynapseML/docs/features/cognitive_services/CognitiveServices%20-%20Overview/).
 
-To make SynapseML's integration with Azure Cognitive Services fast and efficient SynapseML introduces many optimizations for service-oriented workflows. In particular, SynapseML automatically parses common throttling responses to ensure that jobs don’t overwhelm backend services. Additionally, it uses exponential back-offs to handle unreliable network connections and failed responses. Finally, Spark’s worker machines stay busy with new asynchronous parallelism primitives for Spark. Asynchronous parallelism allows worker machines to send requests while waiting on a responses from the server and can yield a tenfold increase in throughput.
+To make SynapseML's integration with Azure Cognitive Services fast and efficient SynapseML introduces many optimizations for service-oriented workflows. In particular, SynapseML automatically parses common throttling responses to ensure that jobs don’t overwhelm backend services. Additionally, it uses exponential back-offs to handle unreliable network connections and failed responses. Finally, Spark’s worker machines stay busy with new asynchronous parallelism primitives for Spark. Asynchronous parallelism allows worker machines to send requests while waiting on a response from the server and can yield a tenfold increase in throughput.
 
 ### Broad ecosystem compatibility with ONNX