Course Recommendation System Using Machine Learning
M. Jahnavi
, Dr. Ch. Suneetha , M. Yashwanth , Naonit Kumar Goutam
Course recommendation, Machine learning, Stemming, Count vectorization, Cosine similarity.
A computer-based algorithm known as a Course Recommendation System helps students choose courses based on their unique interests, academic skills, and desired careers. Making the appropriate decision during formative years is crucial since the outcome will affect the future. This method uses machine learning algorithms to create a list of courses that most closely fit the user's tastes by analyzing user activity data, including ratings and past search history. To recommend the best courses based on their interests, machine learning algorithms including stemming, count vectorization, and cosine similarity are used. The main objective of this paper is to lighten the workload of the students while maintaining their attention.
"Course Recommendation System Using Machine Learning", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 6, page no.1877 - 1881, June-2023, Available :https://ijsdr.org/papers/IJSDR2306255.pdf
Volume 8
Issue 6,
June-2023
Pages : 1877 - 1881
Paper Reg. ID: IJSDR_207430
Published Paper Id: IJSDR2306255
Downloads: 000347087
Research Area: Electronics & Communication Engg.
Country: Hyderabad, Telangana, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
