INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
In today's world, we have an abundance of search
options available to us, making it difficult to select what we
truly need. This is where recommender systems come into play.
These systems utilize various algorithms to filter data and
suggest information that is most relevant to the user. They are
useful customization tools that are frequently updated based on
the preferences of current customers. These systems have
proven to be beneficial in various fields, including e-commerce,
education, entertainment, media, books, films, and productrelated industries. The purpose of this study is to explore
different recommendation techniques, their advantages and
disadvantages, and several performance metrics. Through a
review of various studies, we examine the methodology,
strategies, key aspects of the algorithms used, and potential
areas for future development
Keywords:
Recommendation System , Machine Learning , Algorithms , Development , Media , Education , Python , Jupyter Notebook
Cite Article:
"Product Recommendation System Using Machine Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 7, page no.a557-a562, July-2023, Available :http://www.ijnrd.org/papers/IJNRD2307070.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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