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| Section | Weight | Objectives |
|---|---|---|
| Describe AI workloads and considerations | 15-20% | - Identify features of common AI workloads - Identify guiding principles for responsible AI |
| Describe features of Generative AI workloads on Azure | 15-20% | - Identify responsible AI considerations for generative AI - Describe generative AI concepts - Describe Azure OpenAI Service capabilities |
| Describe features of computer vision workloads on Azure | 15-20% | - Identify common computer vision tasks - Identify Azure AI services for computer vision - Describe Azure capabilities for computer vision |
| Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Describe Azure capabilities for NLP - Identify common NLP tasks - Identify Azure AI services for NLP |
| Describe fundamental principles of machine learning on Azure | 30-35% | - Describe core machine learning concepts - Describe Azure Machine Learning capabilities - Identify common machine learning tasks - Describe features of no-code automated ML |
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NEW QUESTION # 283
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation
Azure Custom Vision is a cognitive service that lets you build, deploy, and improve your own image classifiers. An image classifier is an AI service that applies labels (which represent classes) to images, according to their visual characteristics. Unlike the Computer Vision service, Custom Vision allows you to specify the labels to apply.
Note: The Custom Vision service uses a machine learning algorithm to apply labels to images. You, the developer, must submit groups of images that feature and lack the characteristics in question. You label the images yourself at the time of submission. Then the algorithm trains to this data and calculates its own accuracy by testing itself on those same images. Once the algorithm is trained, you can test, retrain, and eventually use it to classify new images according to the needs of your app. You can also export the model itself for offline use.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/home custom vision - This is a type of computer vision service which helps in building/training models using user provided data Creating an object detection solution with Custom Vision consists of three main tasks. First you must use upload and tag images, then you can train the model, and finally you must publish the model so that client applications can use it to generate predictions.
https://docs.microsoft.com/en-us/learn/modules/detect-objects-images-custom-vision/2-object-detection-azure
NEW QUESTION # 284
You have the Predicted vs. True chart shown in the following exhibit.
Which type of model is the chart used to evaluate?
Answer: C
Explanation:
Explanation
What is a Predicted vs. True chart?
Predicted vs. True shows the relationship between a predicted value and its correlating true value for a regression problem. This graph can be used to measure performance of a model as the closer to the y=x line the predicted values are, the better the accuracy of a predictive model.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-m
NEW QUESTION # 285
What is an example of unsupervised machine learning?
Answer: C
NEW QUESTION # 286
What are two tasks that can be performed by using the Computer Vision service? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,B
NEW QUESTION # 287
Which natural language processing feature can be used to identify the main talking points in customer feedback surveys?
Answer: C
NEW QUESTION # 288
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