- Published on November 2, 2020
- In Deep Tech
Hands-On Guide To Recommendation System Using Collaborative Filtering
Recommendation systems expect to foresee clients' inclinations and predict the most likely product that the users are most likely to purchase and are of interest to them.
- By Ankit Das
Recommendation systems expect to foresee clients' inclinations and predict the most likely product that the users are most likely to purchase and are of interest to them. Organizations utilizing recommendation frameworks centre around expanding deals because of exceptionally customized offers and an upgraded client experience. Netflix, Amazon, and so forth use recommender frameworks to assist their clients with recognizing the right item or films for them.
In this article, we will discuss the recommendation system with its types where we will cover the collaborative filtering method in detail with implementations.
Types Of Recommendation System
1. Collaborative Filtering
Collaborative filtering is used to find similar users or items and provide multiple ways to calculate rating
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Ankit Das
A data analyst with expertise in statistical analysis, data visualization ready to serve the industry using various analytical platforms. I look forward to having in-depth knowledge of machine learning and data science. Outside work, you can find me as a fun-loving person with hobbies such as sports and music.
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