You may find a lot of tutorials which would help you build end to end Machine Learning pipelines. But generally, those tutorials do not mention much about how to maintain the quality of predictions generated from the ML systems.

您可能会发现很多教程，可以帮助您构建端到端的机器学习管道。 但是通常，这些教程并未过多提及如何保持从ML系统生成的预测的质量。

Maintaining the predictive power of the deployed model is deemed to be more difficult than building the ML model from scratch and hence is our topic of discussion today.

与从头开始构建ML模型相比，维持已部署模型的预测能力更加困难，因此，这是我们今天讨论的主题。

But before starting with the details of “model retraining”, let’s have a quick primer on “model training” first:

但是，在详细介绍“模型训练”之前，让我们首先快速了解“模型训练” ：

• Assuming the sufficient h