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Recommendation system Real World Projects using Python
Real World Projects on recommendation systems with data science, machine learning and AI techniques..
This Course Includes
udemy
4.4 (44 reviews )
4h 29m 
english
Online - Self Paced
professional certificate
Udemy
About Recommendation system Real World Projects using Python
Believe it or not, almost _all_ online platforms today uses
recommender systems
in some way or another. So What does “recommender systems” stand for and why are they so useful? Let’s look at the top 3 websites on the Internet : Google, YouTube, and Netfix
: Search results Thats why Google is the most successful technology company today.
YouTube
: Video dashboard I’m sure I’m not the only one who’s accidentally spent _hours_ on YouTube when I had more important things to do! Just how do they convince you to do that? That’s right this is all on account of Recommender systems!
Netflix
: So powerful in terms of recommending right movies to users according to the behaviour of users ! Recommender systems aim to predict users' interests and recommend product items that quite likely are interesting for them. This course gives you a thorough understanding of the Recommendation systems. In this course, we will cover :
Use cases of recommender systems.
Average weighted Technique Recommender System
Popularity-based Recommender System
Hybrid Model based on Average weighted & Popularity
Collaborative filtering.
Content based filtering
and much, much more! Not only this, you will also work on two very exciting projects.
Instructor Support
- Quick Instructor Support for any query within
_2-3 hours_
All the resources used in this course will be shared with you via Google Drive Link How to make most from the course ?
Check out the lecture "Utilize This Golden Oppurtunity , QnA Section !"
What You Will Learn?
- Learn How to tackle Real world Problems.. .
- Learn Collaborative based filtering .
- Learn how to use Correlation for Recommending similar Movies or similar books .
- Learn Content based recommendation system .
- Learn how to use different Techniques like Average Weighted , Hybrid Model etc.. .
- Learn different types of Recommender Systems.