AI 용어집
인공지능 완전 사전
Neural Architecture Search
Automated design and optimization of neural network architectures for specific tasks.
Hyperparameter Optimization
Automated process of searching for the best hyperparameters for a machine learning model.
Automated Data Preprocessing
Systems automating the cleaning, transformation, and normalization of raw data before modeling.
Automatic Feature Selection
Algorithms that automatically identify the most relevant variables for model performance.
Automatic Feature Engineering
Automatic creation of new features from existing data to improve performance.
Automatic Cross-Validation
Systems that automatically optimize cross-validation strategies to assess model robustness.
Automated Ensemble Learning
Automatic combination of multiple models to create more robust and accurate predictions.
AutoML for Time Series
AutoML Specialization for temporal sequential data prediction and analysis.
AutoML for Computer Vision
Tools automating model creation for image classification, detection and segmentation.
AutoML for NLP
Platforms automating model development for natural language processing and analysis.
Cloud AutoML Platforms
Cloud services offering complete AutoML solutions with integrated infrastructure.
Embedded and Edge AutoML
Automatic optimization of models for deployment on resource-constrained devices.
Meta-Learning
Systems that learn to learn, quickly adapting to new tasks with little data.
MLOps Automation
Integration of automation in the complete ML lifecycle, from deployment to maintenance.
Interpretable AutoML
Automatic generation of models balancing performance and prediction interpretability.