化学工程中的机器学习:实践活动

IF 3.5 2区 教育学 Q1 EDUCATION, SCIENTIFIC DISCIPLINES
Vitor Lavor , Fernando de Come , Moisés Teles dos Santos , Ardson S. Vianna Jr.
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引用次数: 0

摘要

介绍了一系列实践活动,这些活动是在化学工程本科生的机器学习入门课程中提出的。活动旨在介绍无监督学习(例如聚类)和有监督学习(如分类和回归)的基本概念。Google Colaboratory是谷歌为促进人工智能和机器学习研究而免费提供的云服务,用于开发这些活动,但拟议的活动可以在本地Python环境中类似地运行。活动中使用的数据集可在Kaggle和加州大学(UCI)等网站上公开获取,还使用了选矿过程化学工程中的一个具体例子。该学生在课程中对ML主题的反应非常积极。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning in chemical engineering: Hands-on activities

A set of hands-on activities, that were proposed in an introduction course to machine learning in a Chemical Engineering undergraduate course, are presented. The activities aimed to introduce basic concepts of unsupervised learning (e.g., clustering) and supervised learning (e.g., classification and regression). Google Colaboratory, a cloud service provided by Google for free to promote research in Artificial Intelligence and Machine Learning, was used to develop these activities, but the proposed activities can be run similarly in a local Python environment. The datasets used in the activities are publicly available on websites such as Kaggle and University of California (UCI), and a specific example in chemical engineering for the ore grinding process was also used. The student's response to the ML topic within the course was very positive.

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来源期刊
CiteScore
8.80
自引率
17.90%
发文量
30
审稿时长
31 days
期刊介绍: Education for Chemical Engineers was launched in 2006 with a remit to publisheducation research papers, resource reviews and teaching and learning notes. ECE is targeted at chemical engineering academics and educators, discussing the ongoingchanges and development in chemical engineering education. This international title publishes papers from around the world, creating a global network of chemical engineering academics. Papers demonstrating how educational research results can be applied to chemical engineering education are particularly welcome, as are the accounts of research work that brings new perspectives to established principles, highlighting unsolved problems or indicating direction for future research relevant to chemical engineering education. Core topic areas: -Assessment- Accreditation- Curriculum development and transformation- Design- Diversity- Distance education-- E-learning Entrepreneurship programs- Industry-academic linkages- Benchmarking- Lifelong learning- Multidisciplinary programs- Outreach from kindergarten to high school programs- Student recruitment and retention and transition programs- New technology- Problem-based learning- Social responsibility and professionalism- Teamwork- Web-based learning
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