IBM Watson AI & Machine Learning Flashcards
6 cards from real IBM Certification practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 IBM Watson AI & Machine Learning flashcards as text
What is AutoAI in IBM Watson Studio?
Answer: An automated machine learning feature that prepares data, selects algorithms, and tunes hyperparameters
AutoAI automatically prepares data, selects the best ML algorithms, and optimizes hyperparameters to generate ranked model pipelines.
In Watson Machine Learning, what is the purpose of a 'scoring endpoint'?
Answer: To provide a REST API URL that accepts input data and returns model predictions
A scoring endpoint is the REST API URL exposed by a deployed Watson Machine Learning model, used to send input data and receive real-time predictions.
Which open-source toolkit, developed by IBM, helps detect and mitigate bias in AI datasets and models?
Answer: AI Fairness 360
AI Fairness 360 (AIF360) is an open-source Python toolkit developed by IBM Research to detect, understand, and mitigate algorithmic bias.
What does 'model drift' mean in the context of Watson OpenScale monitoring?
Answer: The model's prediction accuracy degrades over time as real-world data patterns change
Model drift occurs when a deployed model's performance degrades because the statistical properties of the live input data diverge from the training data.
What type of connection does IBM Watson Studio use to access data stored in IBM Cloud Object Storage?
Answer: Connected data asset via a project connection
Watson Studio accesses IBM Cloud Object Storage data through connected data assets, which are configured as project-level connections.
Which IBM certification exam validates skills in building and operationalizing machine learning solutions on IBM Cloud Pak for Data?
Answer: C1000-143 IBM Certified ML Specialist – Cloud Pak for Data
The IBM Certified Machine Learning Specialist – IBM Cloud Pak for Data exam (C1000-143) validates skills in building and operationalizing ML solutions on the platform.