Components for Artificial Intelligence – Azure AI

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Azure has various modules for the use of artificial intelligence. An example of this is Azure Machine Learning and the aforementioned Azure Databricks. Azure Machine Learning consists of various services such as Azure Cognitive Services, through which image processing and speech processing AIs can be built and trained with little programming effort. In addition, Azure GPU Server offers the training of large deep learning models as well as a complete ML Ops pipeline for stabilization and standardization in AI projects. Azure Databricks is a big data analysis tool in an Apache Spark environment. Azure Databricks has the great advantage that developed AI solutions can be created within a few minutes and are automatically scalable. Projects can be built with deep learning libraries such as PyTorch, Tensorflow or Scikit learn.

There is an Azure Data Factory that handles hybrid data integration, integrates all data serverlessly, and stores this data in Azure Data Lake Storage. AI applications can be built and trained using Azure Databricks. Azure Synapse Analytics is an analytics service that combines data integration, data warehousing, and big data analytics. It allows cameroon consumer email list​ developers to generate various insights for data using AI and offer them as an analytics endpoint. The results can be visualized using Microsoft's Power BI. It enables a complete stack with data management, data processing, AI, and big data analytics and visualization to be quickly created and offered with manageable effort.

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Source: Databricks

In addition to these solutions, there are also ready-made solutions for knowledge mining (Azure Cognitive Search). These enable customers to discover patterns and relationships in their data, evaluate customer motivation and extract keywords.

The Azure Bot Service offers conversational AI, a chatbot that can be adapted to your own scenario. There are also solutions for automatically processing documents, as well as for machine translation. This also includes the ability to automatically convert voice messages into text and vice versa.

Azure Serverless
To save time and resources that are not part of the core business, Microsoft Azure offers serverless services. This frees developers from the tasks of deploying and managing the infrastructure. These are taken over by the cloud provider.