A K-means algorithm for personalized recommendations for higher education courses

With the renewal of the educational concept, personalized education has gradually become a research hotspot, and higher dance course education also needs to adapt to this trend and meet the differentiated learning needs of students through personalized recommendation. In today's society, the precision and efficiency of personalized recommendation of higher dance course education are not high, which greatly affects the accuracy of personalized recommendation of higher dance course education. K-means algorithm in machine learning is an effective personalized recommendation technology for higher dance education. K-means algorithm is used to construct the personalized recommendation technology in the personalized recommendation system of higher dance course education, so as to provide better education matching for higher dance course education and help students learn better skills. Finally, the experimental results show that the K-means algorithm is easy to operate, and the accuracy rate is 97.6%.