Recommender Syste in Python

Are you stressed by poor grades and tight deadlines? We have your back. We can do this or a different assignment for you at an affordable price. Use writing services to score better and meet your deadlines.

Order a Similar Paper Order a Different Paper

Using the files ratings.dat which contains user_id, movie_id, ratings,
timestamp. Users.dat which contains user_id, gender, age, occupation, zip
code and file movies.dat which contains movie_id, title, genres. Can also
identify and incorporate data from other sources for example
The system should be able to recommend 5 movies for a given user. The
system can take as input a user’s info and or ratings of movies and output a
set of 5 recommended movies. Also have to provide answers to the
following questions: 1. Which recommendations approach did you use and
why? Please cite relevant literature (5 points). 2. What
knowledge does your recommender system need in order to function? Did you
use any external data sources, e.g datasets etc? (20 points. 15 for extra
sources and 5 for describing the knowledge needed). 3. Describe how
your algorithm/code works (25 points. 20 for description 5
for code). 4. Evaluate your algorithm, either offline or
with a user study. Decribe the evaluation setup and results (10
points). 5. Reflect on your work. How does your algorithm
perform? How can you improve on it in the future (10points).

I have spent a lot of time on this because this is the first time I am
learning python. So a lot of time is spent just trying to understanding
python including getting the software to work. I have some code but can’t
get it to request user input unless I am overthinking this it is my understanding
that get a request run the code and it outputs recommendations, please help.

We offer CUSTOM-WRITTEN, CONFIDENTIAL, ORIGINAL, and PRIVATE writing services. Kindly click on the ORDER NOW button to receive an A++ paper from our masters- and PhD writers.

Get a 10% discount on your order using the following coupon code SAVE10

Order a Similar Paper Order a Different Paper