Скачать или смотреть SUBSAMPLING - How to pronounce it?

SUBSAMPLING - Avoid mistakes: The right way to say Subsampling in 2023

Subsampling is a technique used in natural language processing and machine learning to reduce the amount of data while maintaining its overall representation and structure.
In this technique, randomly selected data points or examples from a larger dataset are removed or downsampled.
The goal is to create a smaller representative sample of the original dataset that can be used for training or analysis without losing too much important information.
Subsampling can improve the efficiency and speed of algorithms by reducing computational overhead and can help mitigate the effects of class imbalance in classification tasks.
It is commonly used in tasks like word embeddings, text classification, and sentiment analysis.

Pronunciation:
To pronounce 'subsampling', you can try variations like 'suhb-sam-pling' or 'sub-sam-pling'.

Test yourself by speaking the following examples:
1. Subsampling is commonly used in natural language processing tasks to reduce the size of large datasets for faster processing
2. In machine learning, subsampling helps address the challenge of class imbalance by creating a more balanced training set
3. Word embeddings, such as word2vec and GloVe, often employ subsampling to improve computational efficiency and remove redundant information from the training data

Last updated: September, 2023