使用 scikit-learn 进行特征工程处理Feature engineering with scikit-learn

本页提供了两个示例笔记本,演示了如何在 Azure Databricks 上使用 scikit-learn 进行特征工程处理。This page provides two example notebooks that illustrate using scikit-learn on Azure Databricks for feature engineering.

在 Azure Databricks 上将 scikit-learn 与 MLflow 集成配合使用Use scikit-learn with MLflow integration on Azure Databricks

此笔记本演示了一个完整的端到端示例,涉及加载数据、训练模型、分布式超参数优化和模型推理。This notebook shows a complete end-to-end example of loading data, training a model, distributed hyperparameter tuning, and model inference. 它还演示了如何使用 MLflow 和模型注册表。It also illustrates how to use MLflow and the model registry.

在 Azure Databricks 上将 scikit-learn 与 MLflow 集成配合使用Use scikit-learn with MLflow integration on Azure Databricks

获取笔记本Get notebook

在 Azure Databricks 上将 scikit-learn 与 Apache Spark 配合使用Use scikit-learn with Apache Spark on Azure Databricks

此笔记本演示了如何在单个计算节点上使用 scikit-learn。This notebook illustrates how to use scikit-learn on a single compute node.

在 Databricks 上将 scikit-learn 与 Apache Spark 配合使用Use scikit-learn with Apache Spark on Databricks

获取笔记本Get notebook