What you would learn in Recommendation system with Machine Learning/AI using Python course?
You may be surprised to learn that nearly every website today uses recommendations systems in one way or another.
So what do "recommender systems" stand for, and why are they beneficial?
Let's examine the three most popular websites available found on the Internet: Google, YouTube, and Netflix.
Google Results: Search results
This is why Google is by far the most profitable technology company of the moment.
YouTube: Video dashboard
I'm sure that I'm not the only one who's stumbled across hours watching YouTube when I had other tasks to complete! How do they persuade you to take that step?
This is because of the Recommender system!
Netflix: Very powerful in the sense of suggesting suitable films to users based on the users' habits!
Recommender systems are designed to anticipate users' interests and suggest items that will be interesting to them.
This course provides you with an in-depth understanding of Recommendation systems.
In this class, we will discuss :
Recommender systems are used in cases of use.
Average weighted Technique Recommender System
Popularity-based Recommender System
Hybrid Model Based on Average weighted and Popularity
Collaborative filtering.
Filtering based on content
and many, many and much, much more!
However, you'll also get to work on two inspiring projects.
Course Content:
- Learn how to deal with real-world problems.
- Learn Collaborative filtering using Learn Collaborative
- Learn to utilize Correlation for recommending similar Movies or books similar to them.
- Recommendations based on Learn Content
- Learn how to utilize various techniques like Average Weighted, Hybrid Model, and more.
- Discover the different kinds of Recommender Systems
Download Recommendation system with Machine Learning/AI using Python from below links NOW!
