AI学习笔记——机器学习中部分易混淆术语解析
image source from unsplash.com by Paweł Czerwiński
对于机器学习的初学者来说，容易被一些专用术语搞得晕头转向，这篇文章我们就从挑几个容易混淆的概念和术语接解析一下。
1. Batch
在机器学习的过程中，有时候由于样本数量巨大，无法一次性送入模型进行学习，需要分成若干Batch(批次)，将样本分批(Batch)送入模型的学习叫做Batch Learning。一个Batch中样本的数量叫做Batch Size。
Number of Batches = Number of Samples / Batch Size
当然Batch Learning 不一定要遍历所有样本，Random Batch 就是随机从样本中取batch size数量的样本送入模型中进行学习，就有可能出现样本被重复选择的情况。
2. Iteration(Step)
Iteration, Step 和 Epoch 三个概念最容易混淆，Iteration 和 Step 概念是一致的，表示完成一次学习过程。
对于Batch Learning, 学完一个Batch的过程就是完成一个Iteration 或者 Step。
3. Epoch
一个Epoch是指所有样本都完成了一次训练。对于Batch Learning 来说，需要将样本中所有Batch都学完。
One Epoch = Number of Iterations (Number = Number of Batches)
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