Abstract
Machine learning has become a core technology in the field of artificial intelligence with its excellent performance and wide range of applications. Traditional machine learning course teaching models often focus on theoretical explanations and lack sufficient practical guidance, making it difficult for students to apply their knowledge to solve practical problems. This article explores feasible ways to reform the teaching of machine learning courses, by strengthening the close integration of basic knowledge and practical skills, as well as optimizing course evaluation methods, significantly improving students' learning effectiveness and practical application abilities.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
