Google Professional Machine Learning Engineer : Professional-Machine-Learning-Engineer

Google Professional-Machine-Learning-Engineer Exam Syllabus Topics:

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

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Understanding functional and technical aspects of Professional Machine Learning Engineer - Google Data Preparation and Processing

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

• Transformations (TensorFlow Transform)
• Evaluation of data quality and feasibility
• Feature crosses
• Design data pipelines
• Feature engineering
• Data ingestion
• Monitoring/changing deployed pipelines
• Ingestion of various file types (e.g. Csv, json, img, parquet or databases, Hadoop/Spark)
• Visualization
• Data exploration (EDA)
• Data validation
• Data leakage and augmentation
• Class imbalance
• Batching and streaming data pipelines at scale
• Database migration
• Handling outliers
• Data privacy and compliance
• Build data pipelines
• Managing large samples (TFRecords)
• Streaming data (e.g. from IoT devices)
• Feature selection
• Handling missing data
• Statistical fundamentals at scale
• Encoding structured data types

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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.

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