Professional-Machine-Learning-Engineer Google Exam Questions and Free Practice Test

Question 7

You have been asked to develop an input pipeline for an ML training model that processes images from disparate sources at a low latency. You discover that your input data does not fit in memory. How should you create a dataset following Google-recommended best practices?

A. Create a tf.data.Dataset.prefetch transformation

B. Convert the images to tf .Tensor Objects, and then run Datase

C. from_tensor_slices{).

D. Convert the images to tf .Tensor Objects, and then run t

E. dat

F. Datase

G. from_tensors ().

H. Convert the images Into TFRecords, store the images in Cloud Storage, and then use the t

I. data API to read the images for training

Correct Answer:D

Question 8

You recently joined a machine learning team that will soon release a new project. As a lead on the project, you are asked to determine the production readiness of the ML components. The team has already tested features and data, model development, and infrastructure. Which additional readiness check should you recommend to the team?

A. Ensure that training is reproducible

B. Ensure that all hyperparameters are tuned

C. Ensure that model performance is monitored

D. Ensure that feature expectations are captured in the schema

Correct Answer:B

Question 9

You built and manage a production system that is responsible for predicting sales numbers. Model accuracy is crucial, because the production model is required to keep up with market changes. Since being deployed to production, the model hasn't changed; however the accuracy of the model has steadily deteriorated. What issue is most likely causing the steady decline in model accuracy?

A. Poor data quality

B. Lack of model retraining

C. Too few layers in the model for capturing information

D. Incorrect data split ratio during model training, evaluation, validation, and test

Correct Answer:D

Question 10

You work for an online retail company that is creating a visual search engine. You have set up an end-to-end ML pipeline on Google Cloud to classify whether an image contains your company's product. Expecting the release of new products in the near future, you configured a retraining functionality in the pipeline so that new data can be fed into your ML models. You also want to use Al Platform's continuous evaluation service to ensure that the models have high accuracy on your test data set. What should you do?

A. Keep the original test dataset unchanged even if newer products are incorporated into retraining

B. Extend your test dataset with images of the newer products when they are introduced to retraining

C. Replace your test dataset with images of the newer products when they are introduced to retraining.

D. Update your test dataset with images of the newer products when your evaluation metrics drop below a pre-decided threshold.

Correct Answer:C

Question 11

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?

A. Redaction, reproducibility, and explainability

B. Traceability, reproducibility, and explainability

C. Federated learning, reproducibility, and explainability

D. Differential privacy federated learning, and explainability

Correct Answer:B

Question 12

You manage a team of data scientists who use a cloud-based backend system to submit training jobs. This system has become very difficult to administer, and you want to use a managed service instead. The data scientists you work with use many different frameworks, including Keras, PyTorch, theano. Scikit-team, and custom libraries. What should you do?

A. Use the Al Platform custom containers feature to receive training jobs using any framework

B. Configure Kubeflow to run on Google Kubernetes Engine and receive training jobs through TFJob

C. Create a library of VM images on Compute Engine; and publish these images on a centralized repository

D. Set up Slurm workload manager to receive jobs that can be scheduled to run on your cloud infrastructure.

Correct Answer:D

START Professional-Machine-Learning-Engineer EXAM