Basic of ‘Recommender System’ ML :

Recommender System

A recommender system predicts users interest and recommends product that the user may be interested in .

Gathers data from :

  • Explicit ratings that users provides.
  • Implicit search engine queries and purchased histories.
  • Other source of knowledge about the users/ item.

Recommender system is an information-filtering technique that provides users with recommendations for which they might be interested in.

Recommender system act as a solution for your day to day choices.

  • Which websites will you find interesting ?
  • Which degree and university are best for your future ?
  • -Which is the investment for supporting the education of your children ?

Paradigms of Recommender System :

Paradigms of Recommender System
  • Reduce the information overload by estimating relevance.
  • Personalised recommendation : Recommends the most relevant item based on user profile and contextual parameters.
  • Collaboration filtering recommendation : Recommends what’s popular among your peers.
  • Content based recommendation : Displays products similar to the products you have like before.
  • Knowledge – based recommender system : Recommends the products based on user’s requirement.

Collaboration Filtering :

Collaboration filtering system

Collaboration filtering system : Collaboration filtering system makes recommendations based on historic preferences of the users.

User – based Nearest Neighbour : User – based Nearest Neighbour recommends items by finding user to active user.

Measuring User Similarity : Pearson Correlations

Measuring User Similarity : Pearson Correlations
  • Pearson Correlations measure of how strong a relationship is between two variables.
  • Degree of linearity can be determined by using Pearson Correlation.
  • It determines linear component of association between two continuous variables.
  • It has no assumptions about linearity.
  • Pearson’s correlation is not used to determine the strength.

To read “All About Supervised Learning” : https://seeve.medium.com/all-about-supervised-learning-dbe9fe9fb676

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Kartikeya Mishra

Kartikeya Mishra

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All about new technology in fun and easy way so that you can be confident in it and make your own piece of work using this knowledge !