Welcome
IPN-Dharma AI Lab
This is an IPN CIC - DHARMA initiative to provide an Artificial Intelligence Laboratory to motivate researchers, professors and students to take advantage of the courses, resources and tools of the main technology platforms of the industry in the areas of Machine Learning, Data Science, Cloud Computing, Artificial Intelligence and Internet of Things with the purpose of generating a practical experience through a learning model between peers and by objectives.
Level 2: Contextual Knowledge
Explore Natural Language Processing
Natural language processing supports applications that can see, hear, speak with, and understand users. Using text analytics, translation, and language understanding services, Microsoft Azure makes it easy to build applications that support natural language.
Courses in this program
1) Analyze Text with the Text Analytics Service
The Text Analytics service is a cloud-based service that provides advanced natural language processing over raw text for sentiment analysis, key phrase extraction, named entity recognition, and language detection.
Learning objectives:
Learning objectives:
- Learn how to use the Text Analytics service for text analysis.
Estimated effort 1 hour
English language
2) Recognize and Synthesize Speech
Learn how to recognize and synthesize speech by using Azure Cognitive Services.
Learning objectives:
Learning objectives:
- Learn about speech recognition and synthesis.
- Learn how to use the Speech cognitive service in Azure.
3) Translate Text and Speech
Automated translation capabilities in an AI solution enables closer collaboration by removing language barriers.
Learning objectives:
Learning objectives:
- After completing this module, you will be able to perform text and speech translation using Azure Cognitive Services.
4) Create a Language Model with Language Understanding
In this module, we'll introduce you to the Language Understanding service, and show how to create applications that understand language.
Learning objectives:
Learning objectives:
- Learn what Language Understanding is.
- Learn about key features, such as intents and utterances.
- Build and publish a natural-language machine-learning model.