What about making a career with the GCP-PMLE certification? Find out the free GCP-PMLE sample questions, study guide PDF, and practice tests for a successful Google Cloud Platform – Professional Machine Learning Engineer (GCP-PMLE) career start.
These materials are proven and help the candidate to pass the exam on their first attempt.
What Is the Google GCP-PMLE Exam Structure?
The Professional Machine Learning Engineer exam is a multiple-choice exam, with 60 questions. You need to get a 70% mark to pass the Professional Machine Learning Engineer exam. The Google Cloud Platform – Professional Machine Learning Engineer (GCP-PMLE) is suitable for candidates who are interested to learn more on the Cloud. The official price for the exam is $200 USD.
What Should Be Your Study Method for the GCP-PMLE Exam Preparation?
Once you are determined to take the GCP-PMLE exam, you must get ready with a study guide that combines all your necessary actions during the preparation and materials in one place.
Visit the Official Page for More Clarity:
Visiting the official page could feel a simple task, but a candidate must make sure, that he is not missing out any valuable information regarding the GCP-PMLE exam. One must visit the official page at the beginning of their preparation to find out about the training and other online resources.
Work on the GCP-PMLE Syllabus Topics:
The basic action of the GCP-PMLE exam candidate should be going through the syllabus details and making out a chart to cover the syllabus topics on time. When it comes to covering the syllabus topics, books and online resources work best to ace the exam.
Success in the Google GCP-PMLE exam is highly dependent on grasping the syllabus topics from the core. The more grasp you have, the more is the chance to succeed quickly. Do not hurry to learn the exam topics; learn one at a time. You can also target covering two to three topics daily from the core, but make sure that you don’t move to the next topic, until you finish one.
Increase Your Productivity through Routine Making:
How to make your study schedule the most productive? If the aspirant follows a planned routine, he is going to experience a more productive preparation. You might be a student, or a working professional, choose your productive time according to your current work and plan out your productive hours. If you want to enhance your productivity during the preparation, you must set aside your study hours. Focusing on daily study would help to learn the syllabus topics in a better manner.
Develop Writing Habit:
If you develop the habit of writing essential points during the study, you can revise quickly through these notes. Your study routine should be such that you can properly utilize the study resources. Therefore, follow some proven steps to pass the exam.
When Is the Right Time to Explore GCP-PMLE Sample Questions & Mock Tests?
- The potential Google GCP-PMLE certification candidates should not restrict themselves to learning the syllabus topics only. They can add more value to their preparation; if they explore different GCP-PMLE sample questions through PDF format or regular format, their knowledge base could become stronger.
- The best time to explore sample questions is at the end of syllabus completion. Many valuable websites offer trusted and free sample questions for the GCP-PMLE exam preparation.
- The preparation process is always better with these sample questions and practice test combinations. Many aspirants opt for the GCP-PMLE dumps PDF materials and end up losing confidence in the exam hall during the actual exam preparation process.
- You can learn from the dumps materials, but working with GCP-PMLE dumps PDF won’t help to assess your preparation level. Taking GCP-PMLE mock exams would help the aspirant to get ready with the actual exam structure, and a candidate becomes an expert regarding time management through this process.
- Therefore, drop your focus from GCP-PMLE exam related dumps PDF and get valuable insights through Professional Machine Learning Engineer practice tests.
- It is always essential to get the real exam experience before you reach the exam hall.GCP-PMLE practice tests, work best in this regard. Continuous practicing helps in getting familiar with the actual exam structure and makes your journey easy while taking the exam.
- VMExam.com offers one of the most valuable practice tests for self assessment. The time-based practice tests help an aspirant to gain ideas on their time management level and answering capacity. The candidates may face difficulty during initial attempts, but through gradual practice, their knowledge base, speed, and marks improve.
- Don’t lose hope, if you are scoring poor in your initial attempts, take it as learn only approach, and be determined to work on the lacking syllabus sections.
How Does the GCP-PMLE Certification Benefit You?
The purpose of becoming the Google Cloud Platform – Professional Machine Learning Engineer (GCP-PMLE) is not only gaining knowledge. The aspirant earns the maximum advantage when they face any interview. With the Professional Machine Learning Engineer certification on their resume, the credibility of the aspirant is proved to the employers over other non-certified peers. Having the Professional Machine Learning Engineer certification, also helps the aspirants to negotiate well for new job roles or for salary hike.
Here Are Few GCP-PMLE Sample Questions for Your Knowledge:
01. Your team is using a TensorFlow Inception-v3 CNN model pretrained on ImageNet for an image classification prediction challenge on 10,000 images. You will use AI Platform to perform the model training.
What TensorFlow distribution strategy and AI Platform training job configuration should you use to train the model and optimize for wall-clock time?
a) Default Strategy; Custom tier with a single master node and four v100 GPUs.
b) One Device Strategy; Custom tier with a single master node and four v100 GPUs.
c) One Device Strategy; Custom tier with a single master node and eight v100 GPUs.
d) MirroredStrategy; Custom tier with a single master node and four v100 GPUs.
02. 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?
a) Use the Integrated Gradients method to efficiently compute feature attributions for each predicted image.
b) Use K-fold cross validation to understand how the model performs on different test datasets.
c) Use PCA (Principal Component Analysis) to reduce the original feature set to a smaller set of easily understood features.
d) Use k-means clustering to group similar images together, and calculate the Davies-Bouldin index to evaluate the separation between clusters.
03. You are an ML engineer at a media company. You want to use machine learning to analyze video content, identify objects, and alert users if there is inappropriate content.
Which Google Cloud products should you use to build this project?
a) Pub/Sub, Cloud Function, Cloud Vision API
b) Pub/Sub, Cloud IoT, Dataflow, Cloud Vision API, Cloud Logging
c) Pub/Sub, Cloud Function, Video Intelligence API, Cloud Logging
d) Pub/Sub, Cloud Function, AutoML Video Intelligence, Cloud Logging
04. You need to write a generic test to verify whether Dense Neural Network (DNN) models automatically released by your team have a sufficient number of parameters to learn the task for which they were built.
What should you do?
a) Train the model for a few iterations, and check for NaN values.
b) Train the model with no regularization, and verify that the loss function is close to zero.
c) Train a simple linear model, and determine if the DNN model outperforms it.
d) Train the model for a few iterations, and verify that the loss is constant.
05. You work for a gaming company that develops and manages a popular massively multiplayer online (MMO) game.
The game’s environment is open-ended, and a large number of positions and moves can be taken by a player. Your team has developed an ML model with TensorFlow that predicts the next move of each player.
Edge deployment is not possible, but low-latency serving is required. How should you configure the deployment?
a) Use a Cloud TPU to optimize model training speed.
b) Use AI Platform Prediction with a NVIDIA GPU to make real-time predictions.
c) Use AI Platform Prediction with a high-CPU machine type to get a batch prediction for the players.
d) Use AI Platform Prediction with a high-memory machine type to get a batch prediction for the players.
