AI Workloads and considerations

Question 1

Principle for responsible AI

Answer 1

Fairness
Reliability and Safety
Privacy and security
Transparency
Inclusiveness
Accountability

Question 2

Key elements of Microsoft AI

Answer 2

Machine Learning
Anomaly detection
Computer Vision
NLP
Conversational AI

Question 3

Parts of supervised ML

Answer 3

Regression

Classification

Question 4

Parts of unsupervised ML

Answer 4

Clustering

Question 5

types of Compute resources you can use in ML studio

Answer 5

Compute Instance
Compute Clusters
Inference Clusters
Attached Compute

Question 6

Asynchronous service for text recognition

Answer 6

Read API

Question 7

Synchronous service for Text recognition

Answer 7

OCR API

Question 8

Text Analytics is part of NLP or Computer Vision?

Answer 8

is part of NLP

Question 9

four types of entities you can create during authoring of LUIS

Answer 9

Machine Learned
List
RegEx
Pattern.any

Question 10

What information you need to provide to developers to use a Custom Vision model?

Answer 10

Prediction Endpoint
Prediction Key
Model Name
Project ID

Question 11

why should I use Language (within Cognitive Services) instead of Text Analytics, LUIS or QnA Maker?

Answer 11

Language represents a commitment to provide you with the latest natural language capabilities. It consolidates familiar capabilities previously available in Text Analytics, QnA Maker, and LUIS into a unified service. Use these capabilities in a single convenient SDK by creating a Language service resource.

Question 12

How many Principle for responsible AI?

Answer 12

6

Question 13

How many key elements of Microsoft AI?

Answer 13

5