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Exam Details:
The Google Professional Machine Learning Engineer exam is designed to validate the skills and knowledge required for building and deploying scalable, reliable, and efficient machine learning models. The exam is intended for professionals who have experience in machine learning and are interested in pursuing a career as a machine learning engineer.
The exam fee is $200, and candidates have two hours to complete the exam. The passing score is 70%, and the exam is available in English, Japanese, and Korean languages. The exam is delivered through the Google Cloud certification platform, which is a secure and proctored environment.
Exam Objectives:
The Google Professional Machine Learning Engineer exam is designed to evaluate the following areas:
- Designing and implementing machine learning models
- Building and training machine learning models using TensorFlow
- Optimizing and improving machine learning models
- Deploying and integrating machine learning models into production
- Monitoring and troubleshooting machine learning models
- Ensuring the security and compliance of machine learning models
Related Books:
There are several books that can help candidates prepare for the Google Professional Machine Learning Engineer exam. Some of the recommended books are:
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron
- Deep Learning with Python by François Chollet
- The Hundred-Page Machine Learning Book by Andriy Burkov
- Python Machine Learning by Sebastian Raschka and Vahid Mirjalili
- Machine Learning: A Probabilistic Perspective by Kevin Murphy
These books cover various topics related to machine learning, such as data preparation, model building, model evaluation, deep learning, and reinforcement learning. They also provide practical examples and case studies to help candidates understand how to apply machine learning techniques in real-world scenarios.
In addition to these books, candidates can also refer to the official Google Cloud documentation, which provides comprehensive guidance on machine learning models, TensorFlow, and other related topics.
In conclusion, the Google Professional Machine Learning Engineer exam is a challenging but rewarding certification for professionals who want to demonstrate their expertise in building and deploying machine learning models. By understanding the exam objectives, preparing with the recommended books and documentation, and practicing with hands-on exercises, candidates can increase their chances of passing the exam and advancing their careers in machine learning engineering.
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