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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-with-r-u/
课程评论：没有评论
课程名称：使用R进行机器学习 概述： 数据科学家被评选为Glassdoor上最受欢迎的职业，根据Indeed的数据显示，数据科学家的平均薪资在美国超过120,000美元！数据科学是一项充满回报的职业，可以让您解决一些世界上最有趣的问题！本课程旨在为完全没有编程经验的初学者或希望转向数据科学的经验丰富的开发人员提供学习平台。这个全面的课程能够与其它通常价格昂贵的机器学习训练营相媲美，但您现在可以以极低的成本学习所有相关知识！这是数据科学和机器学习最全面的课程之一。 课程内容包括： - 机器学习的介绍 - 机器学习的起源 - 机器学习的使用与滥用 - 伦理考量 - 机器是如何学习的？ - 应用机器学习到您的数据的步骤 - 选择机器学习算法 - 使用R进行机器学习 - 数值数据预测 - 回归方法 - 理解回归 - 示例 - 使用线性回归预测医疗费用 - 数据收集 - 数据探索与准备 - 在数据上训练模型 - 评估模型表现 - 改进模型表现 本课程将教授如何使用R编程，创建惊人的数据可视化，以及如何使用R进行机器学习，是您进入数据科学领域的绝佳起点。
Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems! This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science! This comprehensive course is comparable to other ML bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! this is one of the most comprehensive course for data science and machine learning. We'll teach you how to program with R, how to create amazing data visualizations, and how to use Machine Learning with R!Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making. This training is an introduction to the concept of machine learning and its application using R tool.The training will include the following:Introducing Machine Learninga. The origins of machine learningb. Uses and abuses of machine learningEthical considerationsHow do machines learn?Steps to apply machine learning to your dataChoosing a machine learning algorithmUsing R for machine learningForecasting Numeric Data - Regression MethodsUnderstanding regressionExample - predicting medical expenses using linear regressiona. collecting datab. exploring and preparing the datac. training a model on the datad. evaluating model performancee. improving model performance
