Resource: GitHub - gottagetgit/AI102Files 

Personalizer: 

Use for recommendation.

Azure Personalizer leverages reinforcement learning, an advanced form of artificial intelligence, to deliver tailored experiences to users through data-driven decision-making. Diverging from traditional recommendation engines, it dynamically adjusts in real-time based on user interactions rather than solely relying on historical data.

Computer Vision:

Extract visual text/tag and description from the images.

Identify celebrities and landmarks

Identify Brand(Logo) from an image

Content Moderation: isAdultContent, isRacyContent, isGoryContent(Violent)

Generate Thumbnails: Unlike normal thumbnail, it can generate from a specific area of an image

Text detection from handwritten and OCR

Form recogniser:  Extract data from invoice pdf or receipt

Face detection and its attributes: Identify emotions, Age, Gender, Head Pose- left-right, Glasses, Hair, Facial Hair, Makeup etc., detect a face from a given image within an image contains group of people, Smile in percentage.

Custom Vision

To train and generate a model based on custom images(Classification and object detection).

Video Indexer

What is Azure AI Video Indexer? | Microsoft Learn 

Deep search : search experience across a video library 

Content creation : Create trailers, highlight reels, social media content, or news clips based on the insights Azure AI Video Indexer extracts from your content.

Accessibility: Whether you want to make your content available for people with disabilities or if you want your content to be distributed to different regions using different languages, you can use the transcription and translation provided by Azure AI Video Indexer in multiple languages.

Monetization: Azure AI Video Indexer can help increase the value of videos. For example, industries that rely on ad revenue (news media, social media, and so on) can deliver relevant ads by using the extracted insights as additional signals to the ad server.

Content moderation: Use textual and visual content moderation models to keep your users safe from inappropriate content and validate that the content you publish matches your organization's values. You can automatically block certain videos or alert your users about the content.

Recommendations: Video insights can be used to improve user engagement by highlighting the relevant video moments to users. By tagging each video with additional metadata, you can recommend to users the most relevant videos and highlight the parts of the video that matches their needs.

NLP

Study guide for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution | Microsoft Learn 

Analyze text by using Azure AI Language

Extract key phrases

Extract entities

Determine sentiment of text

Detect the language used in text

Detect personally identifiable information (PII) in text

Process speech by using Azure AI Speech

Implement text-to-speech

Implement speech-to-text

Improve text-to-speech by using Speech Synthesis Markup Language (SSML)

Implement custom speech solutions

Implement intent recognition

Implement keyword recognition

Translate language

Translate text and documents by using the Azure AI Translator service

Implement custom translation, including training, improving, and publishing a custom model

Translate speech-to-speech by using the Azure AI Speech service

Translate speech-to-text by using the Azure AI Speech service

Translate to multiple languages simultaneously

Implement and manage a language understanding model by using Azure AI Language

Create intents and add utterances

Create entities

Train, evaluate, deploy, and test a language understanding model

Optimize a language understanding model

Consume a language model from a client application

Backup and recover language understanding models

Azure AI Services