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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-ml-python/
课程评论：没有评论
课程名称：Python中的数据科学与机器学习：线性模型 课程概述：为什么要学习数据科学？现代企业每天收集和存储大量数据，但许多公司缺乏提取知识和做出决策的工具和能力，这一现象逐渐改变。近年来，数据科学家的需求激增，以至于能够胜任此职位的人才远远不足，导致职位空缺严重。因此，数据科学家的薪资也在持续上涨。 为什么选择这个课程？大多数课程往往过于理论化或实践化，大学课程通常无法培养解决数据科学问题所需的技能，也不够流畅地教授必要的软件使用。同时，许多在线课程和训练营则往往在理论理解方面过于肤浅。本课程结合了这两者的优点：我们将深入理解这些方法的来源和使用原因，并从零开始编写代码，利用最流行的数据科学和机器学习库，明白每个算法的具体工作原理后，再学习如何使用它们。 课程内容包括： - 机器学习和数据科学简介 - 简单线性回归：研究不同现象之间的关系 - 多元线性回归：创建多个变量的模型以研究感兴趣变量的行为 - Lasso回归：多元线性回归的高级版本，能够筛选出最有用的变量 - Ridge回归：更加稳定的多元线性回归版本 - 逻辑回归：最流行的分类与检测算法，研究不同变量与特定类别对象之间的关系 - 泊松回归：分析多个变量如何影响事件发生的次数 - 数据科学中的核心概念（如过拟合与欠拟合、交叉验证、变量准备等） 如果有任何问题，记得我们提供30天退款保证，确保你无需承担风险。我们对这门课程充满信心，相信你会喜欢它。
Why study data science?Companies have a problem: they collect and store huge amounts of data on a daily basis. The problem is that they don't have the tools and capabilities to extract knowledge and make decisions from that data. But that is changing. For some years now, the demand for data scientists has grown exponentially. So much so, that the number of people with these skills is not enough to fill all the job openings. A basic search on Glassdoor or Indeed will reveal to you why data scientist salaries have grown so much in recent years.Why this course?Almost every course out there is either too theoretical or too practical. University courses don't usually develop the skills needed to tackle data science problems from scratch, nor do they teach you how to use the necessary software fluently. On the other hand, many online courses and bootcamps teach you how to use these techniques without getting a deep understanding of them, going through the theory superficially.Our course combines the best of each method. On the one hand, we will look at where these methods come from and why they are used, understanding why they work the way they do. On the other, we will program these methods from scratch, using the most popular data science and machine learning libraries in Python. Only when you have understood exactly how each algorithm works, we will learn how to use them with advanced Python libraries.Course contentIntroduction to machine learning and data science.Simple linear regression. We will learn how to study the relationship between different phenomena.Multiple linear regression. We will create models with more than one variable to study the behavior of a variable of interest.Lasso regression. Advanced version of multiple linear regression with the ability to filter the most useful variables.Ridge regression. A more stable version of multiple linear regression.Logistic regression. Most popular classification and detection algorithm. It will allow us to study the relationship between different variables and certain object classes.Poisson regression. Algorithm that will allow us to see how several variables affect the number of times an event occurs.Central concepts in data science (overfitting vs underfitting, cross-validation, variable preparation, etc).Any questions? Remember that we have a 30-day full money-back guarantee. No risk for you. That's how convinced we are that you will love the course.
