|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/automated-machine-learning-hands-on-automl-for-beginners/
课程评论：没有评论
**课程名称：** AutoML 入门实践 **课程概述：** 本课程旨在为初学者介绍自动化机器学习（AutoML），解答“AutoML 是什么？”、“AutoML 是否会取代数据科学家？”、“如何在 Python 中使用 AutoML ？”以及“有哪些免费可用的 AutoML 选项？”等普遍疑问。 课程将重点介绍各种现有的自动化机器学习（包括深度学习）框架，并提供大量动手实践机会。我们主要关注免费的 AutoML 库，让学员能够跟随学习并自行尝试。课程包含用于回归和分类任务的演示数据集，让我们能针对每个 AutoML 库学习两类监督学习任务。学员也可以尝试使用自己的数据进行 AutoML 实践。 **先修要求：** * 具备 Python 使用经验（即使是 AutoML 也需要少量代码编写）。 **课程不包含内容：** * 机器学习/深度学习基础入门或 Python 基础教学。 * 对每个可调超参数进行深入的理论探讨。 * 提供适用于未来所有项目的“全能解决方案”。 **课程包含内容：** * 提供如何在演示数据集上应用这些库的动手代码示例。 * 针对每个库提供使用时需要注意的具体相关信息。 * 为希望减少重复性任务、节省时间以专注于数据科学生命周期关键步骤的数据科学家或商业人士提供有用的工具。
What is Automated Machine Learning (AutoML)Will Automated Machine Learning replace Datascientists?How to use AutoML in pythonWhat AutoML options are available and free to use?If you are a beginner and want answers to those questions and try AutoML yourself then this course is for you.Here we go through various AutomatedMachine Learning (and Deep Learning) frameworks which are currently available (not an extensive list of course there are many more).The main goal is to get an overview of what AutoML is and how to use it in python. We focus on free AutoML libraries instead of commercial ones so that you can follow along and try them yourself. The course has demo datasets for regression as well as a classification task so we see both supervised learning tasks for each AutoML libary we are going to cover.Feel free to try out Automated Machine Learning with your own data as wellFor this course you should have used Python before (Even AutoML requires us to write a tiny little bit of code)Please also understand what this course is notThis course does not offer:A basic introduction to what is ML/DL or an introduction to pythonAn in-depth theoretic dive into each hyperparameter which can be adjusted / tunedAn all-in-one solution for every project you want to take in the futureThis course does offer:hands on code examples on how to apply those libraries on demo datasetsSpecific relevant information for each library you need to be aware of when you use itHelpful tools for any data scientist of business person who wants to reduce redundant and repetitive tasks and free some time to focus on the main steps in the data science life cyclle
