"Perturbable" is an adjective, while "embedding" is a noun.
Perturbable refers to something or someone that can be disturbed or agitated. It is not very commonly used in everyday language and tends to appear more in academic or technical contexts.
Embedding refers to the act of incorporating an object or element into a larger whole, often used in contexts such as data structures and machine learning. Like "perturbable," "embedding" is more frequently used in technical and written contexts.
Perturbable embedding — это критическая концепция в понимании того, как модели могут реагировать на изменения в данных.
The researchers studied the effects of perturbable embedding on neural networks to improve accuracy.
Исследователи изучали эффекты perturbable embedding на нейронные сети для повышения точности.
In machine learning, perturbable embedding helps in analyzing the robustness of algorithms.
"Perturbable embedding" is not commonly associated with idiomatic expressions due to its highly technical nature. However, the term "embedding" can appear in various idiomatic phrases in the right contexts.
Команда должна была глубоко встроить информацию в свои модели, чтобы обеспечить точность.
Their methods embed data into algorithms seamlessly, making them effective at predictions.
Их методы встраивают данные в алгоритмы плавно, что делает их эффективными в предсказаниях.
It's essential to embed ideas within a framework for clear communication.
Antonyms: Unperturbable, calm.
Embedding:
By understanding "perturbable embedding," one can better approach topics in machine learning and data analysis, where stability and incorporation of information are crucial.