Batch (machine learning)

The set of examples used in one training iteration. The batch size determines the number of examples in a batch.¹

See epoch for an explanation of how a batch relates to an epoch.

Footnotes

developers.google.com/machine-learning/glossary#batch

mini-batch 이 글을 인용: “The batch size of a mini-batch is usually between 10 and 1,000 examples.”
역전파 이 글을 인용: “During the forward pass, the system processes a batch of examples to yield prediction(s).”
ML crash course - Linear regression “Mean squared error: The average of L2 losses across a set of examples.”
Introduction to Machine Learning “Machine learning crash course: If you're ready for an in-depth and hands-on approach to learning more about ML.”
Machine Learning Systems “Machine Learning Systems provides a systematic framework for understanding and engineering machine learning (ML…”
Self-training (machine learning) “Use supervised learning to train a model on the labeled examples.”
Clipping (machine learning) “For example, suppose that <0.5% of values for a particular feature fall outside the range 40–60.”
Generalization (machine learning) “You train a model on the examples in the training set.”
Downsampling (machine learning) “Training on a disproportionately low percentage of over-represented class examples in order to improve model tr…”
기계학습 “2023-12-27 - CI/CD for Machine Learning in 2024: Best Practices to Build, Test, and Deploy”
지도 학습 “Supervised machine learning is analogous to learning a subject by studying a set of questions and their corresp…”
Learning rate “For example, a learning rate of 0.3 would adjust weights and biases three times more powerfully than a learning…”
Mean squared error “Divide the L2 loss by the number of examples in the batch.”
모델 (기계학습) “Unsupervised machine learning also generates models, typically a function that can map an input example to the …”
Minority class (machine learning) “A training set with a million examples sounds impressive.”
Semi-supervised learning “Self-training is one technique for semi-supervised learning.”
손실 함수 이 글을 인용: “During training or testing, a mathematical function that calculates the loss on a batch of examples.”
Interpretability (machine learning) “The ability to explain or to present an ML models reasoning in understandable terms to a human.”
Mean absolute error 이 글을 인용: “Divide the L1 loss by the number of examples in the batch.”
Parameter (machine learning) “For example, learning rate is a hyperparameter.”