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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-in-r-support-vector-machines/
课程评论：没有评论
课程名称：R语言中的机器学习：支持向量机 课程概述： 在本课程中，您将学习如何利用强大的R语言对贷款审批进行分类。我们将实施一个完整的基于支持向量机的机器学习模型，以确定贷款是否应被批准。支持向量机在分类任务中表现出色，尤其适用于判断贷款审批的情况。您将通过分析数据、清洗数据和特征工程来完成这一过程。 为什么选择这门课程？ 随着金融犯罪指控和案件的增加，银行及其他金融机构正在采取措施来遏制这一现象，实施机器学习解决方案是一种有效的方法。本课程将指导您逐步构建完整的机器学习模型，帮助您通过分析614笔贷款的数据集（包括性别、婚姻状况、教育水平、月收入、贷款金额等类别）来推断贷款是否应被批准。课程假设少数特征在分类中占主导地位。 课程内容包括： - 支持向量机简介 - 探索性数据分析 - 类别变量的填补 - 数值变量的填补 - 初始模型创建 - 特征选择 - 以及更多内容！ 通过这个项目，您将掌握使用支持向量机对贷款审批进行分类的技能。
Learn to use the powerful R language to classify loan approvals We will implement a complete support vector machine based ML model to classify loan approvals. These models are highly efficient in classifying whether a loan should be approved or not. You will get to learn Data analysis, data cleaning and feature engineering in one single courseWhy Should You Take This Course?This course will give developers a step by step guide to build a complete machine learning model , as allegations and stories of financial crimes are on the increase, banks and other financial institutions are taking steps to curb it and implementing machine learning solution is a great way to do it. This course will teach you how to deduce if a loan should be approved or not by using the data set of 614 loans. The data set has categories such as gender, marital status, education level, monthly income, loan amount, and so on. The live example is based on the assumption that a small number of features will dominate classifications.The Course IncludesIntroduction to Support Vector MachinesExploratory Data AnalysisImputing Categorical VariablesImputing Numerical VariablesInitial Model CreationFeature SelectionAnd much more!Become Proficient at Classifying Loan Approvals Using Support Vector Machines with this project
