Basic Background about Collaborative Filtering

Collaborative filtering is the process of filtering for information using techniques involving collaboration among multiple agents. Applications of collaborative filtering typically involve very large data sets. Collaborative filtering methods have been applied to many different kinds of data including: sensing and monitoring data, such as in mineral exploration, environmental sensing over large areas or multiple sensors; financial data, such as financial service institutions that integrate many financial sources; or in electronic commerce and web applications where the focus is on user data

In a narrower sense, collaborative filtering is a method of making automatic predictions about the interests of a user by collecting preferences or taste information from many users.



The article covers some good tutorials we came across in python about Collaborative filtering not in any order.





An introduction to recommender systems with Crab: Crab is a ﬂexible, fast recommender engine for Python that integrates classic information ﬁltering recom- mendation algorithms in the world of scientiﬁc Python packages (numpy, scipy, matplotlib). The engine aims to provide a rich set of components from which you can construct a customized recommender system from a set of algorithms. The tutorial is from official documentation of Crab.





Collaborative Filtering : Implementation with Python!: The 2 part tutorial from Artificial intelligence and Python blog aimotion. This blog posts presents an implementation of the collaborative filtering algorithm (CF), that filters information for a user based on a collection of user profiles. Users having similar profiles may share similar interests. For a user, information can be filtered in/out regarding to the behaviors of his or her similar users.





Collaborative Filtering with Python: This is tutorial walks through the implementation of item and user based collaborative filtering scripts in python.





Collaborative filtering made easy: The tutorial walks through the process of translating the simple ideas in paper Slope One Predictors for Online Rating-Based Collaborative Filtering into Python code.





Collaborative filtering recommendation engine implementation in python : The tutorial talks about a basic idea about Collaborative filtering along with the idea of the Long tail phenomenon in recommendation engine. It gives an example in the form of a movie recommendation engine and its implementation in python.