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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-course-data-cleaning-feature-engineering/
课程评论：没有评论
**课程名称：** 数据科学 2023：数据预处理与特征工程 **课程概述：** 现实世界中的数据往往是不完整的、混乱的。这就是为什么数据预处理会占据机器学习建模过程约 70% 的时间。本课程“数据科学课程：数据清洗与特征工程”是一门专注于机器学习建模中最耗时任务——“数据预处理”的硬核课程。如果您想提升数据预处理技能以构建更高性能的机器学习模型，那么本课程正是为您量身打造的。 本课程由经验丰富的数据科学家设计，将一步步地引导您完成数据预处理的全过程，让您深入理解预处理的“为什么”和“如何做”。通过每个教程的学习，您将掌握新的技能，并加深对如何克服数据预处理挑战性方面的理解。 **课程结构：** * **第一部分：** 探索性数据分析 (EDA) - 深入了解您的数据集。 * **第二部分：** 数据清洗 - 基于洞察清洗您的数据。 * **第三部分：** 数据操作 - 生成特征、子集划分、处理日期等。 * **第四部分：** 特征工程 - 为模型准备数据。 * **第五部分：** 使用 Pandas DataFrame 编写函数。 * **奖励部分：** 面向正在求职的数据科学爱好者的面试准备技巧和策略。 **目标学员：** * 任何有兴趣提高数据预处理效率的人。 * 正在学习数据科学，希望更深入理解数据及其处理方法的学习者。 * 希望提升数据预处理技能的初级数据科学家。 * 对数据科学预处理部分感兴趣的任何人。 **不适合人群：** * 希望学习机器学习算法的人。 **课程亮点：** * 专注于数据预处理这一关键领域。 * 由经验丰富的数据科学家授课。 * 提供实用的方法和技巧，解决数据预处理的挑战。 * 结构清晰，循序渐进。 * 包含额外的面试准备指导。
Real-life data are dirty. This is the reason why preprocessing tasks take approximately 70% of the time in the ML modeling process. Moreover, there is a lack of dedicated courses which deal with this challenging taskIntroducing, "Data Science Course: Data Cleaning & Feature Engineering" a hardcore completely dedicated course to the most tedious tasks of Machine Learning modeling - "Data preprocessing".if you want to enhance your data preprocessing skills to get better high-performing ML models, then this course is for you!This course has been designed by experienced Data Scientists who will help you to understand the WHYs and HOWs of preprocessing.I will walk you step-by-step into the process of data preprocessing. With every tutorial, you will develop new skills and improve your understanding of preprocessing challenging ways to overcome this challengeIt is structured the following way:Part 1- EDA (exploratory Data Analysis): Get insights into your datasetPart 2 - Data Cleaning: Clean your data based on insightsPart 3 - Data Manipulation: Generating features, subsetting, working with dates, etc.Part 4 - Feature Engineering- Get the data ready for modelingPart 5 - Function writing with Pandas DarframeBonus Section: A few Interview preparation tips and strategies for data science enthusiasts in the job huntWho this course is for:Anyone who is interested in becoming efficient in data preprocessingPeople who are learning data scientists and want better to understand the various nuances of data and its treatmentBudding data scientists who want to improve data preprocessing skillsAnyone who is interested in preprocessing part of data scienceThis course is not for people who want to learn machine learning algorithms
