6 AI900 finaL SUMMARY

  • Azure Bot Service can import frequently asked questions (FAQ) to question and answer sets. （No）
  • The QnA Maker service can determine the intent of a user utterance. (No)
  • C. Answer questions from multiple users simultaneously.
  • D. You need to ensure that the bot uses user feedback to improve the relevance of the responses over time. active learning
  • object detection.： Returning a bounding box that indicates the location of a vehicle in an image
  • Named Entity Recognition (NER) used to extract dates, quantities, and locations from text.
  • Add professional greetings and other responses to make the bot more user friendly. D. Add chit-chat
  • determine a user's intent? / interpret the meaning of a user input => Language Understanding (LUIS)
  • speech recognition
    • providing closed captions for recorded or live videos
    • creating a transcript of a telephone call or meeting
  • Assigning classes to images before training a classification model is an example of (labeling)
  • Azure Speech Services capabilities
    • B. The Speech-to-Text API provides a batch transcript API that can be used to batch process larger audio files.
    • C. When using the Text-to-Speech API, you can configure speech settings such as speed and volume.
  • Accuracy is the calculated probability of a correct image classification.
  • Two components can you drag onto a canvas （dataset/module)
  • Evaluate a classification model? => A. true positive rate
  • Evaluate a regression model?
    • A. coefficient of determination (R2)
    • C. root mean squared error (RMSE)
  • Azure Automated Machine Learning (AutoML)
    • A. AutoML is used to automatically select the best machine learning algorithm for your dataset.
    • B. You can choose to use either the Python SDK or a no-code user interface to build an AutoML experiment.
  • Azure Language Understanding (LUIS) model response
    • A. A list of intents with a confidence score
    • C. A list of entities extracted from the input question/command.
  • Azure Text Analytics API?
    • A. language detection
    • B. named entity recognition
  • Automated machine learning can automatically infer the training data from the use case provided. (No)
    • Automated machine learning enables you to specify a dataset and will automatically understand which label to predict. (No)
  • A. Classification algorithms use labeled training data to build a model and predict the category (class) of yet unseen data items.
    • D. Classification algorithms can predict both binary and multi-class classification problems.
  • Azure's Computer Vision JSON response
    • A confidence score that indicates how likely the tag correctly matches the content in the image.
  • A primary metric used to compare the results of individual experimental runs.
    • B. A list of blocked algorithms that should be excluded from the training runs.
  • Language - you use to determine a user’s intent
  • Power Virtual Agents - can be used to build no-code apps that use built-in natural language processing models
  • You need to ensure that the model detects when utterances are outside the intended scope of the model. - B. Add utterances to the None intent
  • extract intent from a user input such as “Call me back later”“ => Language
  • generate a narration audio file for each video based on the script => speech synthesis
  • Evaluating the performance of a model, => confusion matrix
  • （NLP) entity is used to identify a phone number? => regular expression
  • Chatbots can support voice input. （Yes)
    • A separate chatbot is required for each communication channel. （No)
  • Identify the intent of a user's requests. => Language service
    • Apply intent to entities and utterances. => Language service
  • NLP => Retrieve support documents / Retrieve order status updates => named entity recognition
  • An AI solution that helps photographers take better portrait photographs by providing feedback on exposure, noise, and occlusion is an example of => facial analysis
  • Object detection can identify the (multiple instance / location / multiple types) of a damaged product in an image.
  • identify groups of rows with similar numeric values in a dataset. => clustering
  • Track multiple versions of a model that was trained by using Azure Machine Learning. => Register the model.
  • ( The Azure portal ) Create a Machine Learning workspace
  • (Machine Learning designer ) Use a drag-and-drop interface used to train and deploy models
  • ( Automated machine learning (automated ML) ) Use a wizard to select configurations for a machine learning run
  • a compute resource should you create before you can run the pipeline
  • Azure Machine Learning designer lets you create machine learning models by Adding and connecting modules on a visual canvas,
  • B. Take a training sample that is representative of the population in the United Kingdom.
  • Specifying granularity in JSON data object is used to indicate the recording pattern of the data. (Yes)
  • XML data format is accepted by Azure Cognitive Search when you are pushing data to the index? (No)
  • Automated machine learning can automatically infer the training data from the use case provided. （N）
    • Automated machine learning enables you to specify a dataset and will automatically understand which label to predict （Y）
  • Question Answering => reate a knowledge base for bots
  • Import from the existing FAQ document into a new knowledge base.
  • Automated machine learning provides you with the ability to include custom Python scripts in a training pipeline. （Yes)
  • The Text Analytics service can identify in which language text is written. (Y)
  • Privacy and Security: Personal data must be visible only to approve.
  • Form Recognizer pre-built receipt model <= Form Recognizer or Cognitive Services resource
  • Use Face service to identify named individual => Use Face to create a group containing multiple images of each named individual, and train a model based on the group
  • What is one aspect that may impair facial detection? => Extreme angles
  • How does the service indicate the location of the faces it detects?
    • A set of coordinates for each face, defining a rectangular bounding box around the face

  • Company wants developers to use only one key and endpoint to access all of the services. => Cognitive Services

  • A Cognitive Services resource support both Computer Vision for text extraction, and Text Analytics for text analysis. => (b) Cognitive Services

  • Object detection model typically return for an image
    • A class label, probability, and bounding box for each object in the image （Y)
    • Azure Machine Learning designer enables you to include custom JavaScript functions. （N）
  • Correct: To use a published model, you need the project ID, the model name, and the key and endpoint for the prediction resource.
  • Create an inference pipeline from the training pipeline
  • You want to use the Computer Vision service to identify the location of individual items in an image. Which of the following features should you retrieve? => a) Objects
  • before deploying the model as a service?
    • Create an inference pipeline from the training pipeline
  • You want to use automated machine learning to train a regression model with the best possible R2 score.
    • a) Set the Primary metric to R2 score
  • You also want the transformation to scale relative to the minimum and maximum values in each column
    • b) Normalize Bata
  • The QnA Maker service can determine the intent of a user utterance. （No)
  • calculated probability of a correct image classification => Confidence