Correct! Azure ML Studio provides serverless compute (auto-managed and scalable), single compute instances (dedicated VMs you control), and compute clusters (scalable clusters for large workloads).
Incorrect. The three compute types in Azure ML Studio are serverless compute, single compute instances, and compute clusters. Each serves different use cases from quick experiments to large-scale training.
Excellent! AutoML supports a comprehensive range of task types including classification, regression, time-series forecasting, computer vision (image classification, object detection), and natural language processing (text classification, named entity recognition).
Incorrect. AutoML supports much more than just basic tasks - it includes classification, regression, time-series forecasting, computer vision, and natural language processing tasks.
Exactly! Azure ML jobs allow you to scale beyond local machine limitations, automatically manage compute resources, provide distributed training capabilities, and integrate with experiment tracking for reproducibility.
Incorrect. The main advantage of jobs is their ability to scale training to powerful compute clusters with automatic resource management and comprehensive experiment tracking capabilities.
Perfect! Azure ML's data labelling tools provide systematic quality control, enable team collaboration, reduce individual bias through consensus mechanisms, and offer comprehensive progress tracking - essential for research environments.
Incorrect. The key benefits include quality control mechanisms, collaboration features, bias reduction through consensus labelling, and comprehensive progress tracking capabilities.
Correct! AutoML systematically creates multiple pipelines in parallel, each testing different machine learning algorithms paired with various feature selections and parameters, then evaluates them based on your specified target metric.
Incorrect. AutoML works by creating multiple pipelines in parallel, systematically testing different algorithms with various parameters and feature selections, then scoring each based on your target metric.
Complete the quiz to see your results.