Building Similarity Based Recommendation System

4.4
estrellas
24 calificaciones
ofrecido por
Coursera Project Network
En este Proyecto guiado, tú:

Understand what is collaborative filtering and how to collect data to build a recommendation system

Understand how to create user item interactions matrix to find which users are most similar to the other users

Build a similarity based recommendation system based on collaborative filtering

Clock2 hour
IntermediateIntermedio
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

Welcome to this 1-hour project-based course on Building Similarity Based Recommendation System. In this project, you will learn how similarity based collaborative filtering recommendation systems work, how you can collect data for building such systems. You will learn what are some different ways you to compute similarity between users and recommend items based on products interacted by other similar users. You will learn to create user item interactions matrix from the original dataset and also how to recommend items to a new user who does not have any historical interactions with the items. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Habilidades que desarrollarás

Data Manipulationcosine similarityRecommender Systems

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Understanding collaborative filtering and dataset

  2. Exploring the dataset

  3. Creating user item interactions matrix

  4. Finding similar users

  5. Creating similarity based recommendation system

  6. Conclusion

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

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