최신 Professional-Machine-Learning-Engineer 무료덤프 - Google Professional Machine Learning Engineer
You work for a textile manufacturer and have been asked to build a model to detect and classify fabric defects. You trained a machine learning model with high recall based on high resolution images taken at the end of the production line. You want quality control inspectors to gain trust in your model. Which technique should you use to understand the rationale of your classifier?
정답: C
설명: (DumpTOP 회원만 볼 수 있음)
You are an ML researcher and are evaluating multiple deep learning-based model architectures and hyperparameter configurations. You need to implement a robust solution to track the progress of each model iteration, visualize key metrics, gain insights into model internals, and optimize training performance.
You want your solution to have the most efficient and powerful approach to compare the models and have the strongest visualization abilities. How should you bull this solution?
You want your solution to have the most efficient and powerful approach to compare the models and have the strongest visualization abilities. How should you bull this solution?
정답: B
설명: (DumpTOP 회원만 볼 수 있음)
Your company manages an application that aggregates news articles from many different online sources and sends them to users. You need to build a recommendation model that will suggest articles to readers that are similar to the articles they are currently reading. Which approach should you use?
정답: B
설명: (DumpTOP 회원만 볼 수 있음)
You are an ML engineer at a manufacturing company. You are creating a classification model for a predictive maintenance use case. You need to predict whether a crucial machine will fail in the next three days so that the repair crew has enough time to fix the machine before it breaks.
Regular maintenance of the machine is relatively inexpensive, but a failure would be very costly.
You have trained several binary classifiers to predict whether the machine will fail, where a prediction of 1 means that the ML model predicts a failure.
You are now evaluating each model on an evaluation dataset. You want to choose a model that prioritizes detection while ensuring that more than 50% of the maintenance jobs triggered by your model address an imminent machine failure. Which model should you choose?
Regular maintenance of the machine is relatively inexpensive, but a failure would be very costly.
You have trained several binary classifiers to predict whether the machine will fail, where a prediction of 1 means that the ML model predicts a failure.
You are now evaluating each model on an evaluation dataset. You want to choose a model that prioritizes detection while ensuring that more than 50% of the maintenance jobs triggered by your model address an imminent machine failure. Which model should you choose?
정답: A
설명: (DumpTOP 회원만 볼 수 있음)
You work at a bank. You need to develop a credit risk model to support loan application decisions. You decide to implement the model by using a neural network in TensorFlow. Due to regulatory requirements, you need to be able to explain the model's predictions based on its features. When the model is deployed, you also want to monitor the model's performance over time. You decided to use Vertex AI for both model development and deployment. What should you do?
정답: A
You have a demand forecasting pipeline in production that uses Dataflow to preprocess raw data prior to model training and prediction.
During preprocessing, you employ Z-score normalization on data stored in BigQuery and write it back to BigQuery.
New training data is added every week.
You want to make the process more efficient by minimizing computation time and manual intervention. What should you do?
During preprocessing, you employ Z-score normalization on data stored in BigQuery and write it back to BigQuery.
New training data is added every week.
You want to make the process more efficient by minimizing computation time and manual intervention. What should you do?
정답: A
설명: (DumpTOP 회원만 볼 수 있음)
You are training an object detection machine learning model on a dataset that consists of three million X-ray images, each roughly 2 GB in size. You are using Vertex AI Training to run a custom training application on a Compute Engine instance with 32-cores, 128 GB of RAM, and 1 NVIDIA P100 GPU. You notice that model training is taking a very long time. You want to decrease training time without sacrificing model performance. What should you do?
정답: D
You recently developed a wide and deep model in TensorFlow. You generated training datasets using a SQL script that preprocessed raw data in BigQuery by performing instance-level transformations of the data. You need to create a training pipeline to retrain the model on a weekly basis. The trained model will be used to generate daily recommendations. You want to minimize model development and training time. How should you develop the training pipeline?
정답: D
Your company manages an ecommerce website. You developed an ML model that recommends additional products to users in near real time based on items currently in the user's cart. The workflow will include the following processes:
1. The website will send a Pub/Sub message with the relevant data and
then receive a message with the prediction from Pub/Sub
2. Predictions will be stored in BigQuery
3. The model will be stored in a Cloud Storage bucket and will be
updated frequently
You want to minimize prediction latency and the effort required to update the model. How should you reconfigure the architecture?
1. The website will send a Pub/Sub message with the relevant data and
then receive a message with the prediction from Pub/Sub
2. Predictions will be stored in BigQuery
3. The model will be stored in a Cloud Storage bucket and will be
updated frequently
You want to minimize prediction latency and the effort required to update the model. How should you reconfigure the architecture?
정답: C
Your team is working on an NLP research project to predict political affiliation of authors based on articles they have written. You have a large training dataset that is structured like this:
You followed the standard 80%-10%-10% data distribution across the training, testing, and evaluation subsets. How should you distribute the training examples across the train-test-eval subsets while maintaining the 80-10-10 proportion?
You followed the standard 80%-10%-10% data distribution across the training, testing, and evaluation subsets. How should you distribute the training examples across the train-test-eval subsets while maintaining the 80-10-10 proportion?
정답: D
설명: (DumpTOP 회원만 볼 수 있음)
You need to design an architecture that serves asynchronous predictions to determine whether a particular mission-critical machine part will fail. Your system collects data from multiple sensors from the machine. You want to build a model that will predict a failure in the next N minutes, given the average of each sensor's data from the past 12 hours. How should you design the architecture?
정답: C
설명: (DumpTOP 회원만 볼 수 있음)
You are training a TensorFlow model on a structured dataset with 100 billion records stored in several CSV files. You need to improve the input/output execution performance. What should you do?
정답: A
설명: (DumpTOP 회원만 볼 수 있음)
You work for a hospital that wants to optimize how it schedules operations. You need to create a model that uses the relationship between the number of surgeries scheduled and beds used. You want to predict how many beds will be needed for patients each day in advance based on the scheduled surgeries. You have one year of data for the hospital organized in 365 rows.
The data includes the following variables for each day:
- Number of scheduled surgeries
- Number of beds occupied
- Date
You want to maximize the speed of model development and testing. What should you do?
The data includes the following variables for each day:
- Number of scheduled surgeries
- Number of beds occupied
- Date
You want to maximize the speed of model development and testing. What should you do?
정답: A
You are developing an ML model to identify your company's products in images. You have access to over one million images in a Cloud Storage bucket. You plan to experiment with different TensorFlow models by using Vertex AI Training. You need to read images at scale during training while minimizing data I/O bottlenecks. What should you do?
정답: D