Git Product home page Git Product logo

movierecommendersystem's Introduction

MovieRecommenderSystem

Building on TuriCreate model creation.

Turicreate is a really powerful Python library that can help in building seamless Machine Learning models in the fields of object detection, recommender system, image classification etc.

In this repository I have TuriCreate library to develope a Basic Movie Recommender System. Recommender Systems can be broadly of 2 types:
1.Content Based Recommender Systems: These type of recommender Systems suggest products based on the input data of the user, thus spanny to a large user base. Itanswers the principle question of "What are the similar products?".
2.Collaborative Filtering Recommender Systems: These type of Recommender Systems answer the question, "Who else?". This means that the model will recommend the products (in this case movie names) that are similar to the other users of the service. It works on the basic principle of users buying similar products today will prefer buying more such common products. They are mostly used in social, consumer-friendly enviornments.Thy are the more popular form of Recommender Systems.

One of the main problems that Recommender Systems face is called Cold Start problem. When a new user, signs up for the service, what recommendations could the service provide him/her? Or the more important question that is, "How do we recommend our products to her/him? and which products?"

This problem is overcome Knowledge-Based Recommender Systems that capture digitally stored knowledge in a company’s backend to match specific user queries by decoding its intents, context, and entities in their backend in the form of datasets. They then apply this to a new user on the basis of an "if-this-then-that" approach.Once the user begins to use the services of the company, the Cold Start problem slowly diminishes.

The following model uses Content Based Recommender Systems.

movierecommendersystem's People

Contributors

parthrangarajan avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.