AI 900 Exam Q&A #20 - Azure AI Fundamentals

Summary

This video by Code with Bibek provides an in-depth exploration of the AI 900 Exam, focusing on Azure AI Fundamentals. The video features a series of questions and answers, spanning topics such as Microsoft’s responsible AI principles, machine learning model tracking in Azure, and natural language processing workloads. The video is structured in a Q&A format, giving listeners direct insights into the type of questions they may encounter on the exam, along with their correct answers. It's an invaluable resource for those preparing for the AI 900 exam, helping learners understand concepts such as fairness in AI, regression models, and computer vision applications.

Highlights

• Explanation of Microsoft’s responsible AI principle: Fairness is key! 🌟
• Clear guidelines on when to use yes or no in regression and classification contexts! 🧐
• The importance of registering models in Azure ML for version tracking! 🔖
• Programming prowess: Why R and Python are the top picks for Azure ML! 🐍
• Uncover computer vision tasks: from detecting brands to color schemes! 🎨

Key Takeaways

• Learn about Microsoft’s responsible AI principle of fairness through Q&A! ⚖️
• Understand regression and classification models with succinct true/false style questions! ✔️❌
• Discover how Azure Machine Learning helps in tracking model versions through model registration! 📝
• Get to know the programming languages like R and Python for Azure ML Designer! 💻
• Identify AI workloads like sentiment analysis and computer vision capabilities! 📊

Overview

In this video, Code with Bibek takes viewers through a targeted review session for the AI 900 Exam, focusing on Azure AI services and principles. Through a sequence of carefully curated questions and answers, exam-takers will grasp Microsoft’s commitment to fairness in AI systems and how this core principle influences their technology.

The tutorial navigates through essential components such as handling different machine learning models, including regression, clustering, and classification. It provides clarity on when and why models need numeric labels, enhancing understanding with straightforward true/false statements. The segment also offers practical guidance on using Microsoft Azure effectively, emphasizing the importance of model registration for efficient version control.

Completing the video, viewers explore Azure's expansive AI functionalities, including language processing and computer vision. They learn to differentiate between various natural language processing tasks like sentiment analysis and key phrase extraction, and discover how these AI tools can be applied to solve real-world problems efficiently. This engaging breakdown offers a structured approach to mastering the AI 900 Exam's topics.

Chapters

• 00:00 - 00:30: Question 191 The chapter titled 'Question 191' addresses a quiz question about Microsoft's responsible AI principles. It asks which principle is violated by cultural denigration, providing options: A) Transparency, B) Fairness, C) Inclusiveness, and D) Accountability. The chapter concludes that the correct answer is option B, Fairness.
• 00:30 - 01:00: Question 192 This chapter focuses on answering two specific questions related to machine learning models. The first question addresses whether labels must be numeric in a regression model, to which the answer is 'yes'. The second question considers whether labels must be used in a clustering model, to which the answer is 'no'.
• 01:00 - 01:30: Question 193 The chapter titled 'Question 193' discusses a query related to classification models, specifically focusing on whether labels need to be numeric. It is clarified that they do not have to be numeric. The chapter involves selecting yes or no for a series of statements to determine their truth, starting with a consideration of the custom vision service.
• 02:00 - 02:30: Question 194 The chapter titled 'Question 194' introduces the use of a certain service to detect objects within an image. The chapter confirms that it is possible to use this service for object detection, as indicated by the answer 'yes.' It discusses the requirement of custom data to train the model, suggesting that users must provide their own datasets to utilize this custom vision service effectively, again affirmed by the answer 'yes.' It also briefly mentions the capability of the service to analyze, although the transcript seems incomplete at this point.
• 02:30 - 03:00: Question 195 The chapter titled 'Question 195' involves a problem-solving scenario where multiple versions of a machine learning model must be tracked using Azure Machine Learning. The options provided for solving this problem are: A) explaining the model or B) provisioning an inference cluster. The text seems to involve considerations for tracking model versions effectively within Azure's ecosystem.
• 03:00 - 03:30: Question 196 The chapter titled 'Question 196' covers multiple-choice questions related to Azure Machine Learning. The focus of these questions is on understanding specific actions or options in the context of Azure Machine Learning, such as registering the training data or the model, and writing custom code for Azure Machine Learning Designer using different programming languages. The correct answer to a question about registering is 'option D: register the model'. The chapter also includes a subsequent question (number 195) about which languages can be used for writing custom code.
• 04:30 - 05:00: Question 197 Chapter 197 is titled 'Question 197'. The chapter discusses different programming languages. Initially, options A, B, C, and D are given as Scala, R, C#, and Python respectively. The correct answers identified in this chapter are R and Python. The transcript also references previous question number 196, which pertains to the development of a predictive model using classification.
• 05:00 - 05:30: Question 198 The chapter discusses a confusion matrix for a model's performance on test data. It focuses on identifying the number of correctly predicted positives (true positives) and false negatives. Two options are given: Option A suggests there are 11 true positives and 13,951 false negatives, while Option B suggests there are 5 true positives and 13,951 false negatives.
• 06:00 - 06:30: Question 199 Chapter Title: Question 199 This chapter discusses the results of a test with options C and D. Option C is identified as the correct answer, having 11 true positives and 1033 false negatives. Despite both options having the same number of false negatives, option C had a higher true positive count, leading it to be deemed the correct answer.
• 07:00 - 07:30: Question 200 Chapter 200: The chapter discusses various tasks that can be performed using computer vision, highlighting the capabilities and applications of this technology. It presents a question about identifying tasks relevant to computer vision from given options, emphasizing detection tasks like identifying brands in images while clarifying that tasks like translating text or predicting stock prices do not typically fall under computer vision.

AI 900 Exam Q&A #20 - Azure AI Fundamentals Transcription

• 00:00 - 00:30 question number 191 cultural denigration is a  violation of which Microsoft   responsible AI principle select the correct option option A transparency option b fairness option C inclusiveness option D accountability the correct answer is option b fairness
• 00:30 - 01:00 question number 192 for each of the following statement select yes  if the statement is true otherwise select no the first statement is for a regression model  labels must be numeric the correct answer is yes the second statement is for a clustering model  labels must be used the correct answer is no
• 01:00 - 01:30 the third statement is for a classification model  labels must be numeric the correct answer is no question number 193 for each of the following statement select yes  if the statement is true otherwise select no the first statement is the custom vision service
• 01:30 - 02:00 can be used to detect objects in  an image the correct answer is yes the second statement is the custom  vision service requires that you   provide your own data to train the  model the correct answer is yes the third statement is the custom  vision service can be used to analyze
• 02:00 - 02:30 video files the correct answer is no question number 194 you need to track multiple versions  of a model that was trained by using   Azure machine learning what should you do option A explain the model option b provision and inference cluster
• 02:30 - 03:00 option C register the training data option D register the model the correct answer is option D register the model question number 195 which all languages can you use to  write custom code for azure machine   learning designer select two correct options
• 03:00 - 03:30 option A Scala option b R option C C# option D python the correct answers are option b R option D python question number 196 you are developing a model to predict  events by using classification you have
• 03:30 - 04:00 a confusion Matrix for the model scored on  test data as shown in the following exhibit   identify how many correctly predicted  positives and false negatives are there option A true positive 11 false negative 13951 option b true true positive 5 false negative 13951
• 04:00 - 04:30 option C true positive 11 false negative 1033 option D true positive 5 false negative 1033 the correct answer is option C true  positive 11 false negative 1033
• 04:30 - 05:00 question number 197 what are the tasks that can be performed by  using computer vision select two correct options option A translate text between languages option b predict stock prices option C detect brands in an image
• 05:00 - 05:30 option D detect the color scheme in an image option e extract key phrases the correct answers are option  C detect branch in an image option D detect the color scheme in an image question number 198 which of the following terms  you will correctly use for data   values that influence the prediction  of a model select the correct option
• 05:30 - 06:00 option A features option b labels option C dependent variables option D identifiers the correct answer is option A features question number 199
• 06:00 - 06:30 which of the listed scenarios is an example  of a webchat bot select the correct option option A translate into English  questions entered by customers at   the kiosk so that the appropriate  person can call the customers back option b accept questions through email  and then root the email messages to the   correct person based on the content of the message
• 06:30 - 07:00 option C from a website interface answer common   questions about scheduled event and  ticket purchases for the music festival the correct answer is option C from  a website interface answer common   questions about scheduled event and  ticket purchases for a music festival question number 200
• 07:00 - 07:30 an app that analyzes social media post to  identify their tone is an example of which   type of natural language processing  workload select the correct option option A entity recognition option b key phrase extraction option C sentiment analysis option D speech recognition
• 07:30 - 08:00 the correct answer is option C sentiment analysis