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movie-recommender's Introduction

movie-recommender

This project examines the Top 250s in IMDB dataset

Methods Used

  • Data Visualization
  • Predictive Modeling
  • EDA
  • etc.

Technologies

  • Python
  • Pandas, numpy
  • Matplotlib, seaborn, altair
  • sklearn
  • re
  • etc.

Project Description

IMDb (an abbreviation of Internet Movie Database) is an online database of information related to films, television series, home videos, video games, and streaming content online. The primary purpose of the dataset is to contain the 250 top-rated data in the categories of movies, series, and games. The movie dataset was used in this project. After preprocessing and analysing the data, created a recommender engine using 'Cosine Similarity'.

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