Google Professional Machine Learning Engineer - Professional-Machine-Learning-Engineer 模擬練習
You work as an analyst at a large banking firm. You are developing a robust scalable ML pipeline to tram several regression and classification models. Your primary focus for the pipeline is model interpretability. You want to productionize the pipeline as quickly as possible. What should you do?
正解: C
You work at a marketing research firm. Your team's current project involves analyzing a large volume of customer surveys. Your team decides to use LLMs in Model Garden and track model training artifacts. You need to determine how to effectively share notebooks within your team and how to orchestrate the ML workflow. You want to use Google-managed services as much as possible. What should you do?
正解: D
解説: (PassTest メンバーにのみ表示されます)
You need to build classification workflows over several structured datasets currently stored in BigQuery. Because you will be performing the classification several times, you want to complete the following steps without writing code: exploratory data analysis, feature selection, model building, training, and hyperparameter tuning and serving. What should you do?
正解: D
解説: (PassTest メンバーにのみ表示されます)
You are an AI engineer with an apparel retail company. The sales team has observed seasonal sales patterns over the past 5-6 years. The sales team analyzes and visualizes the weekly sales data stored in CSV files. You have been asked to estimate weekly sales for future seasons to optimize inventory and personnel workloads. You want to use the most efficient approach. What should you do?
正解: C
解説: (PassTest メンバーにのみ表示されます)
You work at an ecommerce startup. You need to create a customer churn prediction model. Your company's recent sales records are stored in a BigQuery table. You want to understand how your initial model is making predictions. You also want to iterate on the model as quickly as possible while minimizing cost. How should you build your first model?
正解: C
You maintain a credit risk model that scores the company's entire portfolio of 80 million accounts once per month. Results are written to BigQuery for downstream reporting, and there is no interactive consumer of the predictions. Your current design keeps a large online endpoint running continuously. You need to reduce cost without affecting the reporting schedule. What should you do?
正解: D
解説: (PassTest メンバーにのみ表示されます)
While performing exploratory data analysis on a dataset, you find that an important categorical feature has 5% null values. You want to minimize the bias that could result from the missing values. How should you handle the missing values?
正解: A
解説: (PassTest メンバーにのみ表示されます)
You recently developed a deep learning model using Keras, and now you are experimenting with different training strategies. First, you trained the model using a single GPU, but the training process was too slow. Next, you distributed the training across 4 GPUs using tf.distribute.MirroredStrategy (with no other changes), but you did not observe a decrease in training time. What should you do?
正解: A
解説: (PassTest メンバーにのみ表示されます)
You are an ML engineer at a regulated insurance company. You are asked to develop an insurance approval model that accepts or rejects insurance applications from potential customers.
What factors should you consider before building the model?
What factors should you consider before building the model?
正解: B
解説: (PassTest メンバーにのみ表示されます)