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所在平台: Udemy |
课程主页: https://www.udemy.com/course/the-complete-supervised-machine-learning-models-in-r-u/
课程评论：没有评论
**课程名称：** The Complete Supervised Machine Learning Models in R **课程概述：** 本课程将全面讲解在R语言中实现的各类监督式机器学习模型。课程强调数学原理的重要性，认为它是成为优秀数据科学家的基石。因此，课程将深入剖析每种模型背后的数学原理，并通过R语言实现进行实践。 学习者不仅能掌握在R中实现特定模型的技巧，还能学会构建实际项目中的模型，并评估其准确率。通过比较不同模型在特定问题上的表现，找出准确率最高的最优模型。 课程还将重点关注数据处理的重要性，讲解如何构建高质量数据集、移除无效特征，以提高机器学习模型的精度和可靠性。 完成本课程后，学习者将精通R语言中所有类型的监督式机器学习模型。 **核心内容：** * **监督式机器学习模型的R语言实现：** 涵盖各类主流模型。 * **模型背后的数学原理：** 深入理解算法的内在逻辑。 * **模型评估与比较：** 学习如何评估模型准确率并选择最佳模型。 * **高质量数据集构建：** 掌握数据预处理和特征工程技术，提升模型性能。 **学习目标：** * 熟练掌握R语言中监督式机器学习模型的实现。 * 深入理解机器学习模型的数学原理。 * 能够独立构建和评估实际应用中的机器学习模型。 * 提高数据处理和特征工程的能力，构建高质量数据集。
In this course, you are going to learn all types of Supervised Machine Learning Models implemented in R Programming Language. The Math behind every model is very important. Without it, you can never become a Good Data Scientist. That is the reason, I have covered the Math behind every model in the intuition part of each Model.Implementation in R is done in such a way so that not only you learn how to implement a specific Model in R Programming Language but you learn how to build real times models and find the accuracy rate of Models so that you can easily test different models on a specific problem, find the accuracy rates and then choose the one which give you the highest accuracy rate.The Data Part is very important in Training any Machine Learning Model. If the Data Contains Useless Entities, it will take down the Precision Level of your Machine Learning Model. We have covered many techniques of how to make high quality Datasets and remove the useless Entities so that we can get high quality and trustable Machine Learning Model. All this is done in this Course.Hence, by taking this course, you will feel mastered in all types of Supervised Machine Learning Models implemented in R Programming Language.I am looking forward to see you in the course..Best
