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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-in-ms-excel/
课程评论：没有评论
课程名称：Excel中的机器学习 概述：欢迎参加Excel机器学习课程！机器学习正在塑造我们的日常生活，是技术创新中最重要的特征之一。本课程的目的是让您掌握在Microsoft Excel中应用的最新机器学习方法，为您提供数据科学和机器学习的新思维方式。这个课程非常适合作为机器学习职业生涯的起点，您将理解一些初步概念并获得实践经验。我们将从零基础开始，一起持续从头到尾开发新技能。在课程中，我们将使用信用风险数据实施一个完整的数据科学项目。该项目包含约40,000名消费者的数据及其特征，如教育水平、年龄、婚姻状况、居住地、是否拥有房产等有用信息。您将深入探索这些数据，并可以自行实践。此外，您将获得宝贵的资源，包括讲座、作业、测验、幻灯片以及有关建模方法的文献回顾。让我们开始看看课程结构吧！
Hi and welcome to the Machine Learning with Excel course,Machine Learning is shaping our everyday lives and it one of the most important features of innovationsin technology. The purpose of this course is to equip you with the newest methods that are applied inMachine Learning by Using Microsoft Excel. It will introduce you to a different way of thinking aboutdata science and machine learning. This is a good way to start a career in Machine Learning since youwill understand some initial concepts and gain some hands-on experience on it. I am extremely happyshare with you everything that I know about Machine Learning with Excel. I promise you it is going to beworth it and you will gain a valuable set of knowledge and skills by attending this course.This is the only course in Udemy where Machine Learning is applied in Microsoft Excel. The reason whywe chose to go with Excel is because we know that many of you are already familiar with it. We will startfrom ground zero and together we will continuously develop new skills from the beginning to the end ofthis course. In this course together we will implement a complete data science project from start tofinish using Credit Risk Data. For this course we have data for around 40,000 consumers and a lot ofcharacteristics about them such as: their level of education, their age, their marital status, where theylive, if they own a home, and other useful details. We will get our hands dirty with these data andexplore them in depth and you can practice all this on your own too. Moreover, you will gain access tovaluable resources such as lectures, homework, quizzes, slides as well as some literature review inregard to the modelling approaches. Let's go ahead now and see how the course structure looks like!
