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Kamus lengkap Kecerdasan Buatan

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AutoML (Automated Machine Learning)

Process of automating the complete machine learning lifecycle, from data preparation to model deployment, reducing human intervention.

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Google Cloud AutoML

Google's cloud platform offering pre-trained AutoML services for vision, NLP, and translation without requiring deep ML expertise.

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Azure Machine Learning Automated ML

Microsoft Azure service that automates algorithm selection, feature engineering, and hyperparameter optimization.

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Amazon SageMaker Autopilot

AutoML feature in SageMaker that automatically explores different solutions to find the best predictive model.

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AutoML Pipeline

Automated sequence of data processing, model training, and evaluation steps in a reproducible workflow.

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Meta-learning in AutoML

Approach where AutoML systems learn from previous experiences to improve their performance on new tasks.

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AutoML Ensembling

Automatic technique for combining multiple models to improve robustness and overall predictive performance.

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Time Series AutoML

Specialization of AutoML for time series forecasting with automatic handling of seasonality and trends.

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Computer Vision AutoML

AutoML solutions specialized in classification, object detection, and image segmentation without deep expertise in computer vision.

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NLP AutoML

AutoML platforms dedicated to natural language processing for text classification, sentiment analysis, and entity recognition.

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Transfer Learning Automation

Automation of the knowledge transfer process from pre-trained models to new specific tasks.

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AutoML Model Interpretability

Integrated tools in AutoML platforms to explain model decisions and ensure prediction transparency.

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