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Question 206 - Professional Machine Learning Engineer discussion

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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?

A.
Train a model for object detection by using Vertex Al AutoML.
Answers
A.
Train a model for object detection by using Vertex Al AutoML.
B.
Train a model for image classification by using Vertex Al AutoML.
Answers
B.
Train a model for image classification by using Vertex Al AutoML.
C.
Develop the model training code for object detection and tram a model by using Vertex Al custom training.
Answers
C.
Develop the model training code for object detection and tram a model by using Vertex Al custom training.
D.
Develop the model training code for image classification and train a model by using Vertex Al custom training.
Answers
D.
Develop the model training code for image classification and train a model by using Vertex Al custom training.
Suggested answer: D

Explanation:

Image classification is a task where the model assigns a label to an image based on its content, such as ''stop sign'' or 'speed limit'1.Object detection is a task where the model locates and identifies multiple objects in an image, and draws bounding boxes around them2. Since your dataset consists of images that were cropped to show one out of ten different traffic signs, you are dealing with an image classification problem, not an object detection problem. Therefore, you need to train a model for image classification, not object detection.

Vertex AI AutoML is a service that allows you to train and deploy high-quality ML models with minimal effort and machine learning expertise3.You can use Vertex AI AutoML to train a model for image classification by uploading your images and labels to a Vertex AI dataset, and then launching an AutoML training job4.However, Vertex AI AutoML does not allow you to tune the model during each training run, as it automatically selects the best model architecture and hyperparameters for your data4.

Vertex AI custom training is a service that allows you to train and deploy your own custom ML models using your own code and frameworks5. You can use Vertex AI custom training to train a model for image classification by writing your own model training code, such as using TensorFlow or PyTorch, and then creating and running a custom training job. Vertex AI custom training allows you to tune the model during each training run, as you can specify the model architecture and hyperparameters in your code, and use Vertex AI Hyperparameter Tuning to optimize them .

Therefore, the best option for your scenario is to develop the model training code for image classification and train a model by using Vertex AI custom training.

Image classification | TensorFlow Core

Object detection | TensorFlow Core

Introduction to Vertex AI AutoML | Google Cloud

AutoML Vision | Google Cloud

Introduction to Vertex AI custom training | Google Cloud

[Custom training with TensorFlow | Vertex AI | Google Cloud]

[Hyperparameter tuning overview | Vertex AI | Google Cloud]

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asked 18/09/2024
Yenziwe Yengwa
43 questions
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