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| Section | Weight | Objectives |
|---|---|---|
| Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
| Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|
| Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|
| Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
>> AI-900 Exam Objectives Pdf <<
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NEW QUESTION # 150
brectly completes the sentence.
Answer:
Explanation:
Explanation:
NEW QUESTION # 151
You have a dataset that contains information about taxi journeys that occurred during a given period.
You need to train a model to predict the fare of a taxi journey. What should you use as a feature?
Answer: B
Explanation:
The label is the column you want to predict. The identified Featuresare the inputs you give the model to predict the Label.
Example:
The provided data set contains the following columns:
passenger_count: The number of passengers on the trip is a feature.
trip_time_in_secs: The amount of time the trip took. You want to predict the fare of the trip before the trip is completed. At that moment, you don't know how long the trip would take. Thus, the trip time is not a feature and you'll exclude this column from the model.
trip_distance: The distance of the trip is a feature.
payment_type: The payment method (cash or credit card) is a feature. fare_amount: The total taxi fare paid is the label.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/predict-prices
NEW QUESTION # 152
You need to identify street names based on street signs in photographs.
Which type of computer vision should you use?
Answer: B
NEW QUESTION # 153
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
This question is based on identifying Natural Language Processing (NLP) workloads, which is a fundamental topic in the Microsoft Azure AI Fundamentals (AI-900) certification. According to the official Microsoft Learn module "Describe features of natural language processing (NLP) workloads on Azure", NLP enables computers to understand, interpret, and generate human language - both written and spoken.
* A bot that responds to queries by internal users - YesThis is an example of a natural language processing workload because it involves understanding and generating human language. A chatbot interprets user input (queries written or spoken) using language understanding and text analytics, and then produces appropriate responses. On Azure, this can be implemented using Azure AI Language (LUIS) and the Azure Bot Service, both core NLP technologies.
* A mobile application that displays images relating to an entered search term - NoThis application involves searching for or displaying images, which falls under the computer vision workload, not NLP.
Computer vision focuses on analyzing and interpreting visual data like photos or videos, while NLP deals with language and text processing.
* A web form used to submit a request to reset a password - NoA password reset form involves structured input fields and user authentication, not natural language understanding or generation. It's part of standard web development and identity management, not an NLP-related process.
Therefore, based on Microsoft's AI-900 curriculum definitions:
# The only true NLP example is the bot responding to user queries, since it processes and understands natural language input to generate conversational output.
NEW QUESTION # 154
You need to develop a chatbot for a website. The chatbot must answer users' questions based on the information in the following documents:
A product troubleshooting guide in a Microsoft Word document
A frequently asked questions (FAQ) list on a webpage
Which service should you use to process the documents?
Answer: A
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/QnAMaker/Overview/overview
NEW QUESTION # 155
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