Natural Language Processing Workloads and Azure AI Language Service
Description
Understanding NLP applications, Azure AI Language service capabilities, sentiment analysis, entity recognition, key phrase extraction, and language understanding
Learning Objectives
Learners will identify features and applications of common NLP workload scenarios including key phrase extraction, entity recognition, sentiment analysis, language modeling, and translation. They will understand Azure AI Language service capabilities and be able to describe implementation approaches for various NLP tasks.
Topics (8)
Learning about statistical language models, neural language models, and transformer architectures
Learning about automatic speech recognition, voice synthesis, and audio processing
Learning about statistical MT, neural MT, and real-time translation systems
Learning about Speech-to-Text, Text-to-Speech, and speech translation in Azure
Learning about emotion detection, polarity classification, and aspect-based sentiment analysis
Learning about Azure Text Analytics, Language Understanding, and custom NLP models
Learning about automatic keyword extraction, topic modeling, and text summarization techniques
Learning about person, location, organization recognition and custom entity extraction