Recommender


Project background

A movie rental company has a list of movies that users watch and users' rating data for the film. It recommends that system services can be quickly recommended to each user according to the user's watch list and previous ratings, personalized recommendation of the movie, the enhancement of user outlook and the improvement of the revenue of the film leasing company.

Solution

BeyondLearning® recommender provides personalized recommendation for each user, and helps users to obtain interesting products, information and services through artificial intelligence. This allows media, e-commerce, news, reading, online education and other industries effectively improve click-through rate, marketing efficiency, user stickiness, and conversion rate.

Instructions

Please contact us if you encounter any problems using the service.

1. Install docker package

> For Windows
For detailed steps to install docker on Windows systems, see https://hub.docker.com/editions/community/docker-ce-desktop-windows
> For Ubuntu
apt-get install docker
> For CentOS / RHEL
yum install docker
> For MacOS
dwnload the dmg file from below link:
https://download.docker.com/mac/stable/Docker.dmg
OR
brew cask install docker

2. Pull image from docker hub

docker pull beyondlearning/recommender

3. Run image

docker run -p 8083:80 -dit --rm beyondlearning/recommender

4. Browser website

Browser with address http://<docker machine ip>:8083 to view the updated website.