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Understanding functional and technical aspects of Professional Machine Learning Engineer - Google ML Model Development

The following will be discussed in Google Professional-Machine-Learning-Engineer exam dumps:

• Hardware accelerators
• Distributed training
• Scale model training and serving
• Tracking metrics during training
• Model generalization
• Retraining/redeployment evaluation
• Modeling techniques given interpretability requirements
• Model performance against baselines, simpler models, and across the time dimension
• Transfer learning
• Model explainability on Cloud AI Platform
• Unit tests for model training and serving
• Build a model
• Overfitting
• Productionizing
• Choice of framework and model
• Training a model as a job in different environments
• Scalable model analysis (e.g. Cloud Storage output files, Dataflow, BigQuery, Google Data Studio)

Reference: https://cloud.google.com/certification/guides/machine-learning-engineer

Exam Details

The Google Professional Machine Learning Engineer exam is two hours long. The candidates can expect multiple-choice as well as multiple-select questions in their delivery of the certification test. The exam is currently given to the learners in the English language. To register for and schedule it, you need to pay $200 (plus applicable taxes). While registering for the test, the potential applicants will be offered to select the convenient mode of exam delivery: an online proctored session from a remote location or an in-person proctored session at the nearest testing center.