Project Overview

This repository documents my journey in building a Natural Language Processing (NLP) solution using Azure AI Language as part of the Microsoft Ignite: Azure AI Language assessment. The project aimed to leverage Azure AI Language services to interpret the semantic meaning of written or spoken language. Here's an overview of the modules covered in this project:

Modules Included:

1. Analyze text with Azure AI Language: Learned to detect language, analyze text sentiment, and extract key phrases, entities, and linked entities using Azure AI Language service.

2. Create question answering solutions with Azure AI Language: Explored question answering capabilities and built applications where users can ask questions using natural language and receive appropriate answers.

3. Build a conversational language understanding model: Trained a model to extract meaning from natural language, defining intents, utterances, and entities. Provisioned Azure resources for Azure AI Language and trained, tested, published, and reviewed the model.

4. Develop an app with Azure AI Language: Published and consumed Azure AI Language Understanding model predictions from client applications.

5. Create a custom text classification solution: Built a custom text classification project using Azure AI Language service, tagging data, training, and deploying a model.

6. Create a custom named entity extraction solution: Built a custom entity recognition solution to extract entities from unstructured documents, labeling data, training, and deploying an entity extraction model.

7. Translate text with Azure AI Translator service: Provisioned a Translator resource, understood language detection, translation, and transliteration, and defined custom translations.

8. Create speech-enabled apps with Azure AI services: Utilized Azure AI Speech service to build speech-enabled applications, focusing on speech-to-text and text-to-speech APIs.

9. Translate speech with the Azure AI Speech service: Provisioned Azure resources for speech translation, generated text translation from speech, and synthesized spoken translations.

Achievements:

• Developed a natural language processing solution using Azure AI Language to interpret written and spoken language.
• Explored various modules to analyze text sentiment, build question answering solutions, and develop conversational language understanding models.
• Utilized Azure AI Language services to provision resources, define intents and entities, train models, and deploy solutions.
• Demonstrated proficiency in building effective NLP solutions with Azure AI Language.
• Microsoft Ignite Achievement: Successfully completed the Azure AI Language assessment, showcasing expertise in deploying AI solutions on the Azure platform.
• Badge Link: Microsoft Ignite Achievement