Movie Recommendation System using Collaborative Filtering

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Neste projeto guiado, você irá:

Learn to create, train and evaluate a recommendation engine with Scikit-Surprise

Learn to clean, analyse and use real-word datasets for recommendation systems

Clock1 hour 25 minutes
CloudSem necessidade de download
VideoVídeo em tela dividida
Comment DotsInglês
LaptopApenas em desktop

With the amount of available online content ever-increasing and all the platforms trying to grab your attention by giving you personalized recommendations, recommendation engines are more important than ever. In this project-based course, you will create a recommendation system using Collaborative Filtering with help of Scikit-surprise library, which learns from past user behavior. We will be working with a movie lense dataset and by the end of this project, you will be able to give unique movie recommendations for every user based on their past ratings. This project is best suited for anyone who is venturing into data science and is curious as to how recommendation engines work. This project will be a great addition to your portfolio to showcase your real-world hands-on experience with recommendation systems as we would be working with a real-world dataset.

Habilidades que você desenvolverá

Data ScienceCollaborative FilteringMachine LearningPython ProgrammingRecommender Systems

Aprender passo a passo

Em um vídeo reproduzido em uma tela dividida com a área de trabalho, seu instrutor o orientará sobre esses passos:

  1. Set up required modules and get them ready for use. Become familiar with the guided project interface

  2. Import real-world dataset and clean it

  3. Do exploratory data analysis on the dataset

  4. Remove the unwanted ratings from the dataset and thus do Dimensionality Reduction

  5. Create trainset and antiset from the data

  6. Train your model on your data and see its performance

  7. Make predictions and recommend the best movies for each user

Como funcionam os projetos guiados

Sua área de trabalho é um espaço em nuvem, acessado diretamente do navegador, sem necessidade de nenhum download

Em um vídeo de tela dividida, seu instrutor te orientará passo a passo

Perguntas Frequentes – FAQ

Perguntas Frequentes – FAQ

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