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所在平台: Udemy |
课程主页: https://www.udemy.com/course/getting-started-with-matlab-machine-learning/
课程评论：没有评论
课程总结：初学者的MATLAB机器学习入门 本课程名为《初学者的MATLAB机器学习入门》，旨在帮助初学者搭建机器学习的基础，使用MATLAB这一许多研究人员和数学专家的首选语言。课程内容包括以下几个方面： 1. **MATLAB环境准备**：指导学员如何为机器学习准备MATLAB工作环境，并展示如何与MATLAB工作区进行交互。 2. **数据处理**：学习数据清洗、挖掘和分析各种数据类型，并了解如何在绘图中展示数据值。 3. **回归技术**：掌握不同类型的回归技术，并学习如何使用MATLAB函数应用于数据分析。 4. **神经网络基础**：理解神经网络的基本概念，并进行数据拟合、模式识别和聚类分析。 5. **特征选择与提取**：探索降维的特征选择和提取技术，以提升机器学习模型的性能。 在课程结束时，学员将通过涉及主要机器学习算法的实际案例，将所学知识整合起来，能够自信地使用MATLAB进行机器学习。 关于讲师Giuseppe Ciaburro，他拥有那不勒斯大学的化学工程硕士学位以及那不勒斯第二大学的声学和噪声控制硕士学位，现在在“路易吉·范维特利大学”下的建筑环境控制实验室工作。Giuseppe在编程领域拥有超过15年的工作经验，精通Python、R和MATLAB，并在声学和噪声控制方面是专家。他具有丰富的电子学习和计算机课程教学经验，并在相关领域有多篇出版物。他目前正在研究机器学习在声学和噪声控制中的应用。
MATLAB is the language of choice for many researchers and mathematics experts when it comes to machine learning. This video will help beginners build a foundation in machine learning using MATLAB. You'll start by getting your system ready with the MATLAB environment for machine learning and you'll see how to easily interact with the MATLAB workspace. You'll then move on to data cleansing, mining, and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll learn about the different types of regression technique and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction to improve performance. By the end of the video, you'll have learned to put it all together via real-world use cases covering the major machine learning algorithms and will be comfortable in performing machine learning with MATLAB. About the Author Giuseppe Ciaburro holds a Master's degree in chemical engineering from Università degli Studi di Napoli Federico II, and a Master's degree in acoustic and noise control from Seconda Università degli Studi di Napoli. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli." He has over 15 years' work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in Python and R, and he has extensive experience of working with MATLAB. An expert in acoustics and noise control, Giuseppe has wide experience in teaching professional computer courses (about 15 years), dealing with e-learning as an author. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He is currently researching Machine Learning applications in acoustics and noise control.
