Lesson 2: Intro to AI Fundamentals w/Azure

Question 1

Anomaly Detection

Answer 1

Detecting data points that do not align with a recognized pattern across a set of data points.

Question 2

API

Answer 2

Application programming interfaces that are exposed to help multiple applications and systems interact with each other.

Question 3

Autonomous

Answer 3

An autonomous system is a system that can accomplish a task without human involvement during the execution of the task.

Question 4

Azure Cognitive Services

Answer 4

A suite of AI Services targeting specialized AI workloads to help developers implement AI capabilities into their solution with minimal AI and ML expertise.

Question 5

Azure Machine Learning

Answer 5

A cloud-based service that delivers a platform supporting the creation and deployment of Machine Learning Models.

Question 6

Computer Vision

Answer 6

A domain of artificial intelligence focused on processing and understanding visual inputs through complex machine learning algorithms.

Question 7

Dataset

Answer 7

A dataset is a collection of data that is used to train the machine during the AI and ML processes.

Question 8

Experiment

Answer 8

In the context of AI and ML, experiment refers to using the AI and ML processes to see if a particular question can be answered with AI and ML, or a hypothesis can be supported or validated.

Question 9

Go

Answer 9

An abstract strategy-based board game of significance in AI due to AI beating a top-seated GO master.

Question 10

Intent

Answer 10

An intent represents the action the user wants to execute. It usually refers to a preferred action when a user delivers a sentence to be interpreted by the machine.

Question 11

Jupyter Notebook

Answer 11

A virtual notebook environment where developers can write notes and combine live code and visualizations into a single document.

Question 12

Machine Learning Model

Answer 12

A machine learning model is a logic that has been trained to recognize certain types of patterns.

Question 13

What is the standard acronym for: Machine Learning Operations

Answer 13

MLOps

Question 14

Machine Learning Operations (MLOps)

Answer 14

The practice involves the automation of processes required to build and deliver end-to-end Machine Learning Models and experiences.

Question 15

Natural Language Processing:

Answer 15

A domain of artificial intelligence focused on understanding human language and helping computers and humans interact through human language.

Question 16

Turing Test

Answer 16

A test where a human tested interacts with two entities, one machine, and one human, without knowing which one is which. The goal of the test is to assess if the tester can identify which one is the machine. If the tester can not determine the machine or is not sure, the machine passes the test.