AI 용어집
인공지능 완전 사전
AutoML (Automated Machine Learning)
Process of automating the complete machine learning lifecycle, from data preparation to model deployment, reducing human intervention.
Google Cloud AutoML
Google's cloud platform offering pre-trained AutoML services for vision, NLP, and translation without requiring deep ML expertise.
Azure Machine Learning Automated ML
Microsoft Azure service that automates algorithm selection, feature engineering, and hyperparameter optimization.
Amazon SageMaker Autopilot
AutoML feature in SageMaker that automatically explores different solutions to find the best predictive model.
AutoML Pipeline
Automated sequence of data processing, model training, and evaluation steps in a reproducible workflow.
Meta-learning in AutoML
Approach where AutoML systems learn from previous experiences to improve their performance on new tasks.
AutoML Ensembling
Automatic technique for combining multiple models to improve robustness and overall predictive performance.
Time Series AutoML
Specialization of AutoML for time series forecasting with automatic handling of seasonality and trends.
Computer Vision AutoML
AutoML solutions specialized in classification, object detection, and image segmentation without deep expertise in computer vision.
NLP AutoML
AutoML platforms dedicated to natural language processing for text classification, sentiment analysis, and entity recognition.
Transfer Learning Automation
Automation of the knowledge transfer process from pre-trained models to new specific tasks.
AutoML Model Interpretability
Integrated tools in AutoML platforms to explain model decisions and ensure prediction transparency.