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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practical-ai-and-machine-learning-with-model-builder-automl/
课程评论：没有评论
课程名称：使用Model Builder AutoML的实用人工智能和机器学习 课程概述：本课程旨在帮助学员理解监督机器学习过程中基础概念。你将学习到复杂的主题，包括：探索性数据分析、数据转换与特征缩放、评估指标、算法、训练者和模型、欠拟合与过拟合、交叉验证、正则化等。与以往通过演示文稿观看概念不同，本课程将让你通过实际的机器学习练习来理解这些概念。我们将使用一种非云端的机器学习工具Model Builder，配合Visual Studio，过程中无需编写代码（除了最后一课）。尽管编码量不大，学员仍能深入掌握复杂的机器学习概念。 本课程要求学员至少对监督和自主机器学习的概念有一定的理论了解，目标是通过实践训练强化基础的理论知识。所教授的内容是机器学习的基础，将在今后的学习中持续相关，无论选择何种机器学习平台或编程语言。过程中你还将接触到Visual Studio、代码项目、解决方案和微软的机器学习生态系统，这些仅是附带收益。课程的重点在于机器学习本身，而不是使用的工具。 如果你已经进行过机器学习或训练过模型，本课程可能对你来说较为基础。尽管本课程可能包含你之前未接触的基础知识，但请注意，该课程主要面向初学者和中级AI爱好者。
In this course, you will get to understand the foundational concepts that underlie the supervised machine-learning process. You will get to understand complex topics such as:Exploratory Data Analysis, Data Transformation and Feature Scaling, Evaluation Metrics, Algorithms, trainers, and models,Underfitting and Overfitting, Cross-validation, Regularization, and much moreYou will see these concepts come alive by doing a practical machine-learning exercise, rather than by looking at presentations. We will be using a non-cloud-based machine-learning tool called Model Builder, inside of Visual Studio. There will be zero coding involved (except for the very last lesson). But even though there is little coding involved, you will still get a very detailed understanding of complex machine-learning concepts.This course requires you to have at least some theoretical exposure to the concepts of supervised and unsupervised machine learning. This course is designed to build on a basic, theoretical understanding of machine learning by doing a practical machine-learning exercise. The concepts taught in this course are foundational and will be relevant in the future, regardless of what machine learning platform or programming language you use. In the process, you will also get some exposure to Visual Studio, code projects, solutions, and the Microsoft Machine Learning ecosystem. But that is just a side benefit. This course focuses on machine learning itself, not the tools that are used.If you've already done any kind of machine learning or trained a model, this course might be too basic for you. This course may contain foundational knowledge that you may not have been taught before, but please be aware that this course is geared toward beginner and intermediate-level AI enthusiasts.
