Calculating Weighted Averages - Java Programming: Build a Recommendation System

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Calculating Weighted Averages - Java Programming: Build a Recommendation System
Java Programming and Software Engineering Fundamentals Specialization
Ever wonder how Netflix decides what movies to recommend for you? Or how Amazon recommends books? We can get a feel for how it works by building a simplified recommender of our own!

In this capstone, you will show off your problem solving and Java programming skills by creating recommender systems. You will work with data for movies, including ratings, but the principles involved can easily be adapted to books, restaurants, and more. You will write a program to answer questions about the data, including which items should be recommended to a user based on their ratings of several movies. Given input files on users ratings and movie titles, you will be able to:

1. Read in and parse data into lists and maps;
2. Calculate average ratings;
3. Calculate how similar a given rater is to another user based on ratings; and
4. Recommend movies to a given user based on ratings.
5. Display recommended movies for a given user on a webpage.
Data Structure, Interfaces, Software Design, Java Programming
Outstanding specialization, Excellent explanation of the concepts and programs, Interesting assignments. Highly recommend this one.,THe courses really tested my overall knowledge of other courses that I have done in past 3 months. REally great learning. Thank you.
In your fourth step, you will complete your recommendation engine by finding users in the database that have similar ratings and weighting their input to provide a more personal recommendation for the users of your program. Once you complete this step, you could request ratings of movies from those you know, run your program, and give them recommendations tailored to their own interests and tastes!
Calculating Weighted Averages - Java Programming: Build a Recommendation System
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