Topic 1 Question 237
You are developing a model to identify traffic signs in images extracted from videos taken from the dashboard of a vehicle. You have a dataset of 100,000 images that were cropped to show one out of ten different traffic signs. The images have been labeled accordingly for model training, and are stored in a Cloud Storage bucket. You need to be able to tune the model during each training run. How should you train the model?
Train a model for object detection by using Vertex AI AutoML.
Train a model for image classification by using Vertex AI AutoML.
Develop the model training code for object detection, and train a model by using Vertex AI custom training.
Develop the model training code for image classification, and train a model by using Vertex AI custom training.
ユーザの投票
コメント(9)
- 正解だと思う選択肢: D
Not A or B since automl doesnt provide you without flexibility to tune.
Not C because object detection is not required since the images are cropped to a single traffic light
👍 16pikachu0072024/01/12 - 正解だと思う選択肢: C
Correct: C
The phrases "identify traffic signs in images extracted from videos" and "images that were cropped to show one out of ten different traffic signs" suggest that this is an image detection problem. The first phrase appears to have the same meaning as "images with," and the second phrase suggests that only one type of traffic sign was used in the problem, indicating that it cannot be used in a multi-class problem. For all these reasons, I believe the best option is C.
👍 3guilhermebutzke2024/02/15 My answer: C
The phrases "identify traffic signs in images extracted from videos" and "images that were cropped to show one out of ten different traffic signs" suggest that this is an image detection problem. The first phrase appears to have the same meaning as "images with," and the second phrase suggests that only one type of traffic sign was used in the problem, indicating that it cannot be used in a multi-class problem. For all these reasons, I believe the best option is C.
👍 2guilhermebutzke2024/02/15
シャッフルモード