Building Similarity Based Recommendation System

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27 個評分
提供方
Coursera Project Network
在此指導項目中,您將:

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
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

  • Data Manipulation
  • cosine similarity
  • Recommender Systems

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  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

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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