Analysis & Recommendation
Recommendation systems are among the most popular applications of data science. They are used to predict the Rating or Preference that a user would give to an item.
Almost every major company has applied them in some form or the other: Amazon uses it to suggest products to customers, YouTube uses it to decide which video to play next on auto-play, and Facebook uses it to recommend pages to like and people to follow.
we have 2 datasets:
1-credits contains movie cast and crew members
2-movies contain all the descriptions and information about the movie('overview', 'budget',' Genre', etc)
Analyze a movie, provide information about it, and recommend similar movies based on the genre, tone, and overall feel of the analyzed movie.
The analysis was about:
Movie Genre listing from the highest to the lowest:
All Movies have a Keyword that specifies or gives a hint about what the movie is talking about or what the storytelling
that is the most frequent Keywords:
Country and the movie productions count:
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Highest vote counts movies:
Highest 20 Movie in popularity:
Budget ranges and what is the most frequent one for a budget:
The relationship between the budget and revenue:
Movies:https://thecleverprogrammer.com/wp-content/uploads/2020/05/tmdb_5000_movies.csv
Credits:https://thecleverprogrammer.com/wp-content/uploads/2020/05/tmdb_5000_credits.csv