机器学习工程师

用 Python 中的 scikit-learn 提升你的机器学习技能。 在这门互动课程中使用真实世界数据集，学习如何做出强大的预测！

了解 MLOps 如何将机器学习模型从本地笔记本带到生产环境中运行，并创造实际业务价值。

Unix 命令行帮助用户以新方式组合现有程序、自动化重复任务，并在集群和云上运行程序。

Dive into agriculture using supervised machine learning and feature selection to aid farmers in crop cultivation and solve real-world problems.

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

Perform a machine learning experiment to find the best model that predicts the temperature in London!

学习使用提取、转换和加载原则构建高效、性能优异且可靠的数据管道。

Ensure high data quality in data science and data engineering workflows with Python's Great Expectations library.

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

This course covers everything you need to know to build a basic machine learning monitoring system in Python

了解 Docker 入门，掌握它在数据专业人士工具箱中的重要性。 了解 Docker 容器、镜像等内容。

Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control