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所在平台: Udemy |
课程主页: https://www.udemy.com/course/feature-engineering-case-study-in-python/
课程评论：没有评论
**课程名称：** Python特征工程案例研究 **课程概述：** 本课程深入探讨特征工程在机器学习中的核心作用。您将学习如何从原始数据中提取最大价值，有效地分离信号与噪声，从而优化模型性能。课程内容涵盖连续型和类别型特征的处理，包括数据清洗、标准化和转换。您还将掌握如何处理缺失值、移除异常值、创建指示变量以及转换特征。课程最后部分将指导您如何为模型准备特征，并通过四种不同的特征工程策略比较其对模型性能的影响。 **学习要点：** * 什么是特征工程？ * 数据探索与可视化 * 现有特征的清洗 * 新特征的创建 * 特征标准化 * 特征工程对模型性能的影响对比 **学习方式：** 本课程是一本实用的实践指南，旨在通过“做中学”的方式赋能您的特征工程技能，并直接应用于Python。强烈建议学员亲手实践教程中的所有示例，因为机器学习实践本质上是编程，而编程是一项实践性极强的活动。观看课程如同看电影将难以获得实质性收获。
Course OverviewThe quality of the predictions coming out of your machine learning model is a direct reflection of the data you feed it during training. Feature engineering helps you extract every last bit of value out of data. This course provides the tools to take a data set, tease out the signal, and throw out the noise in order to optimize your models. The concepts generalize to nearly any kind of machine learning algorithm. In the course you'll explore continuous and categorical features and shows how to clean, normalize, and alter them. Learn how to address missing values, remove outliers, transform data, create indicators, and convert features. In the final sections, you'll to prepare features for modeling and provides four variations for comparison, so you can evaluate the impact of cleaning, transforming, and creating features through the lens of model performance.What You'll LearnWhat is feature engineering?Exploring the dataPlotting featuresCleaning existing featuresCreating new featuresStandardizing featuresComparing the impacts on model performanceThis course is a hands on-guide. It is a playbook and a workbook intended for you to learn by doing and then apply your new understanding to the feature engineering in Python. To get the most out of the course, I would recommend working through all the examples in each tutorial. If you watch this course like a movie you'll get little out of it. In the applied space machine learning is programming and programming is a hands on-sport. Thank you for your interest in Feature Engineering Case Study in Python.Let's get started!
