Google Professional-Machine-Learning-Engineer Exam Questions : Google Professional Machine Learning Engineer

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:

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

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

Professional Machine Learning Engineer - Google Certification Path

The associate level certification is focused on the fundamental skills of deploying, monitoring, and maintaining projects on Google Cloud. This certification is a good starting point for those new to cloud and can be used as a path to professional level certifications.

Professional certifications span key technical job functions and assess advanced skills in design, implementation, and management. These certifications are recommended for individuals with industry experience and familiarity with Google Cloud products and solutions.

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