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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-cleaning-with-polars/
课程评论：没有评论
**课程名称：** 使用 Polars 进行数据清洗 **课程概述：** 数据科学工作中 80% 的时间都用于数据清洗。使用不干净或混乱的数据构建机器学习模型会导致模型性能不准确。因此，掌握各种真实世界数据集的清洗方法非常重要。本课程旨在帮助您提升数据处理和清洗技能，为您提供必要的工具。 **课程亮点：** * **Polars 深度解析：** 学习使用 Polars——一个闪电般快速的 Python DataFrame 库，轻松处理大型数据集。 * **五种不同数据集实战：** 通过五个独特的数据集，学习如何清洗不同类型的混乱数据。 * **全面的数据转换技巧：** 掌握数据类型转换、删除不必要列/行、处理缺失值（删除或替换）以及应对异常值等关键数据清洗技术。 * **职场就绪技能：** 课程内容紧贴实际需求，帮助您掌握任何类型数据集的清洗方法，为模型构建做好准备。
Description80% of data science work is data cleaning. Building a machine learning model using unclean or messy data can lead to inaccuracies in your model performance. Therefore, it is important for you to know how to clean various real-world datasets. If you're looking to enhance your skills in data manipulation and cleaning, this course will arm you with the essential skills needed to make that possible. This course is carefully crafted to provide you with a deeper understanding of data cleaning using Polars, a new blazingly fast DataFrame library for Python that enables you to handle large datasets with ease.Five Different DatasetsAll clean datasets are the same, but every unclean dataset is messy in its own way. This course includes five unique datasets and gives you a walkthrough of how to clean each one of themData TransformationData cleaning is about transforming the data from changing data types to removing unnecessary columns or rows. It's also about dropping or replacing missing values as well as handling outliers. You will learn how to do all that in this course.Ready-to-Use SkillsThe lectures in this course are designed to help you conquer essential data cleaning tasks. You'll gain job-ready skills and knowledge on how to clean any type of dataset and make it ready for model building.
