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所在平台: Udemy |
课程主页: https://www.udemy.com/course/r-programming-for-complete-data-science-and-machine-learning/
课程评论：没有评论
课程名称：为完整数据科学和机器学习而设的R编程 课程概览：本课程将引导您深入学习R编程，并结合机器学习的概念，了解数据科学的应用。尽管数据科学家和机器学习专家希望能灵活便捷地工作，但由于学习曲线陡峭，许多学生常常感到疲惫和困惑。尤其是机器学习中的数学和统计学内容，往往让人感到困扰。R语言和Python在行业中交替使用，但R在统计包的支持上具有独特优势。在这个数据无处不在的现代社会，学习R和机器学习对于清理和筛选有用数据以进行未来预测至关重要。在就业市场中，掌握R编程的求职者比其他编程语言的求职者在统计和机器学习领域更具竞争力。 课程设计适合所有水平的学生，尤其是正在学习和实操的学生。模块I专注于R编程，包括理论与R Studio IDE的实践工作；模块II则独立讨论监督学习和无监督学习算法。每节课内容基于实时真实案例和数据集，帮助您更好理解。 在第一模块中，您将学习： - R的基础知识、安装及“HELLO WORLD！” - 变量与数据类型 - 运算符 - 数据结构 - 原子向量及其所有操作 - 列表及其所有操作 - 数组及其所有操作 - 矩阵及其所有操作 - 数据框及其所有操作 - 因子及其所有操作 - 控制结构（if语句及其家族） - Switch语句 - 循环（For、while、repeat） - 跳转语句 - 函数及其类型 - 数据可视化 - 使用ggplot2进行高级数据可视化 在第二模块中，您将学习： - 机器学习简介和数据集 - 回归分析 - 线性回归 - 多元线性回归 - 多项式回归 - 支持向量回归 - 分类 - 逻辑回归 - 支持向量分类 - K近邻分类 - 聚类 - 层次聚类算法 - K均值聚类算法 - 关联规则 - Apriori算法 - Eclat算法 - F-P增长算法 总结而言，本课程适合所有技能水平的学员，即便是对编程语言和统计学一无所知的人也可参与。学习永无止境，专注于技能与技术将使您的生活更加舒适和便捷！期待在课程中见到您。 祝好， Fahad Hussain
The whole journey of the course is all about R Programming first, then Machine Learning including the concept of Data Science using R programming. Flexibility and ease are the desire of every Data Scientist or machine learning expert, but because of steep learning, student get tired and overwhelmed. The journey of machine learning especially got confused due to Math and Statistics behind! R and Python are interchangeably used in the industry where R has its own strengthen with respect to the statistical packages support on it. In the modern world where the Data is around everywhere study of R with Machine Learning play a tremendous role to clean and filter out the data to make it useful for future predication. In the Job market if you know R programming your chances are high to get job as compare to other languages in the filed of statistics and machine learning. The Course designed is such a way, that will be useful for all level specially student who are learning and under working on it.This separate session in Module I is all about R programming including Theoretical and Practical work using R Studio IDE, whereas in Module II, the individually session of supervised and unsupervised machine learning algorithm will be discussed. The discussion of each session based on live and real life example and dataset to make you understand in better way.The Course has Two Module, in Module-I you will learn:What is R, Installation, HELLO WORLD!Variable and Data typesOperators in RData StructureAtomic vector All OperationsList All OperationsArray All OperationsMatrices All OperationsData Frame All OperationsFactors All OperationsControl structures (if statements / Family)Switch statementsLoops (For, while, repeat)Jump StatementsFunctions & TypesData VisualizationAdvance Data Visualization using ggplot2.In Module-II you will learn:Machine Learning Introduction and DatasetRegressionLinear RegressionMultiple Linear RegressionPolynomial RegressionSupport Vector RegressionClassificationLogistic RegressionSupport Vector ClassificationK Nearest Neighbors ClassificationClusteringHierarchical Clustering AlgorithmK Means Clustering AlgorithmAssociationApriori AlgorithmEclat AlgorithmF-P Growth AlgorithmIn Final words, the Couse is useful for all skill level, even you do not know about any programming language and Statistics behand it. As we know Learning never end so be focus on skill and technology to make your life comfortable and easy! Now, I will be very excised to see you in the course.Regards,Fahad Hussain
