The latest Microsoft AI-900 Azure AI Fundamentals certification actual real practice exam question and answer (Q&A) dumps are available free, which are helpful for you to pass the Microsoft AI-900 Azure AI Fundamentals exam and earn Microsoft AI-900 Azure AI Fundamentals certification.
Exam Question 91
What information does the client application need to use a published custom vision model?
Project ID, Model name, Prediction endpoint, Prediction key
Exam Question 92
trained to classify individual objects within an image and identify their location with a bounding box
Exam Question 93
What information does an object detection model return?
Class of object identified, probability score of the object classification, coordinates of a bounding box for each object
Exam Question 94
What’s the difference between object detection and image classification?
Image classification is a machine learning based form of computer vision in which a model is trained to categorize images based on the primary subject matter they contain. Object detection goes further than this to classify individual objects within the image, and to return the coordinates of a bounding box that indicates the objects location
Exam Question 95
What are some uses of object detection?
Evaluating the safety of a building by looking for fire extinguishers or other emergency equipment, creating software for self-driving cars or vehicles with lane assist capabilities, medical imaging such as an MRI or x-rays that can detect known objects for medical diagnosis
Exam Question 96
What are the 3 main tasks for creating an object detection solution with custom vision?
Uploading and tagging images, training model, publishing model
Exam Question 97
What resources to you need to create an object detection solution?
Custom Vision(can be either training or prediction resource)
Cognitive Services(can be used for training, prediction or both)
Exam Question 98
What are key considerations for tagging training images?
having sufficient images from multiple angles and making sure bounding boxing are tightly defined
Exam Question 99
involves identifying regions of an image that contain a human face, typically by returning bounding box coordinates that form a rectangle around the face
Exam Question 100
moves beyond simple face detection, some algorithms can also return other information such as facial landmarks(nose, eyes, eyebrows, lips). These can be used as features with which to train a machine learning model from which you can infer information about a person such as their gender, age or emotional state.