Exploring additional ML capabilities in Azure Synapse
As we have seen, AutoML accelerates the adoption of ML in your existing analytics environment, especially if you are getting started with ML. It tests your data with different combinations of algorithms and parameters to find the model that offers the best result possible. However, if you’re an experienced ML engineer, there are other options available in Azure Synapse that will help you build your own projects while leveraging the parallel compute capabilities in Apache Spark and proximity with your Data Explorer pool data. Let’s briefly describe these options.
Using pre-trained models with Cognitive Services
Azure Cognitive Services is a cloud offering from Microsoft that provides APIs that developers can use to consume pre-trained artificial intelligence models in their applications. These pre-trained models facilitate building applications for computer vision, speech, language, and decision-making tasks....