Explanation

Explanation
Batch anomaly detection is a type of anomaly detection that scans the entire dataset at once for outliers and unusual patterns. Batch anomaly detection is suitable for offline analysis of historical data, such as sensor data from the previous 24 hours. Batch anomaly detection can use various techniques, such as statistical methods, machine learning methods, or hybrid methods, to identify anomalies in the data123.

Explanation:

Box 1: Text Analytics
The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
Box 2: Translator
Translator is a cloud-based neural machine translation service that is part of the Azure Cognitive Services family of REST APIs. Translator can be used with any operating system and powers many Microsoft products and services used by thousands of businesses worldwide to perform language translation and other language-related operations.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-language
https://docs.microsoft.com/en-us/azure/cognitive-services/translator/translator-overview