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popularity-recommender

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Deep Learning is a technology used in machine learning and is applied to a number of signal and image applications. The main purpose of the work presented is to apply the concept of a Deep Learning algorithm namely, Convolutional Neural Networks (CNN) in image classification. A recommendation engine filters the data using different algorithms an…

  • Updated Mar 8, 2021
  • Jupyter Notebook

A recommendation model which finds popular movies according to votes and ratings given to each movie, recommends movies to the user according to the user's previous interactions using K-means Clustering and cosine similarity and also suggests movies to the user based on the likes of similar other users in the dataset using Pearson similarity index.

  • Updated Jan 25, 2021
  • Jupyter Notebook

This work involved building a pipeline of recommender systems comprising of Popularity based recommender, KNN similarity based Clustering recommender, Item-Item association based recommender, Bi-Partite graph based association recommender, Neural Graph based Collaborative Filtering and Neural Embedding based Collaborative filtering.

  • Updated Oct 19, 2021
  • Jupyter Notebook

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