GCP Machine Learning Engineer Flashcards: 317 Key Terms

317 flashcards for the Google Cloud Professional Machine Learning Engineer exam, one for every key term of the Concept Maps. Flip a card, say how well you knew it, and spaced repetition brings it back just before you would forget it: after 1 day, then 3, 7 and 16 days. Once you know a term, you also get the reverse card: the description, and you find the term. Your progress stays on your own device.

The Section 1 cards (Architecting low-code AI solutions) are free, no sign-up. The other sections come with the full Google Cloud Professional Machine Learning Engineer Study Kit.

Free Section 1 cards: 55 terms

• Agent Platform (formerly Vertex AI)
• BigQuery ML
• Agent Platform AutoML
• Tabular Workflows
• AutoML data requirements
• Optimization objective
• Training budget
• AutoML forecasting
• Exporting AutoML models to the edge
• Classification
• Regression
• Forecasting
• Forecasting with extra signals
• Pretrained forecasting (AI.FORECAST)
• Clustering
• Matrix factorization
• Anomaly detection
• Dimensionality reduction
• TRANSFORM clause
• Feature engineering and selection
• ML.PREDICT and ML.FORECAST
• ML.EVALUATE
• Fine-tuning Gemini in BigQuery
• Data splitting
• Hyperparameter tuning in BigQuery ML
• Explaining predictions
• Remote models
• Imported models
• Online serving for BigQuery ML models
• Model Garden
• Models as a service
• Self-deployed open models
• Gemini
• Gemini image models and Veo
• Open models like Gemma
• Prompt prototyping in the console
• Model cards
• Document AI
• Vision API
• Translation API
• Natural Language API
• Speech-to-Text and Text-to-Speech
• Video Intelligence API
• Document AI processors
• API before custom model
• Tuning for a use case
• Model choice for cost and latency
• Context caching
• Batch inference
• Provisioned Throughput
• Global endpoint
• Dynamic shared quota and 429s
• Grounding
• Structured output
• Safety settings

See how these terms connect on the free Section 1 Concept Map. New to the exam? Read the GCP Machine Learning Engineer study guide.