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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:

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

Preparation Process

The candidates for the Google Professional Machine Learning Engineer certification can find everything they need to efficiently prepare for the qualifying test on the official website. The most recommended resource offered by the vendor is the Machine Learning Engineer learning path. It contains both lessons and practical labs for a comprehensive understanding of the exam content. Moreover, the students can take advantage of the sample questions designed to help the potential test takers familiarize themselves with the possible exam questions. Finally, the applicants can opt for the Machine Learning Engineer Prep Webinar to join the Google experts and recently certified professionals for the tips and insights on the Machine Learning models, data processing systems, solution quality, and more.

For more info read reference:

Google Web Services Website

Career Bonuses

The Google Professional Machine Learning Engineer certification proves that the successful candidates possess sufficient knowledge and skills to design and create scalable solutions for optimal performance. Some of the job roles that these individuals can consider include a Data Engineer, a Senior Data Engineer, a Machine Learning Engineer, a Technical Solutions Engineer, a Software Engineer, and a Cloud Infrastructure Engineer, among others. The median salary that the certificate holders can count on is around $140,000 per annum.

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

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