- For earlier sections, just know some basic arithmetic
- Be proficient in 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
Google: 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 !”
Who this course is for:
- Data Scientists
- Data Analysts
- Machine learning Engineer
- Anyone who wants to deep dive into data science.
- Students and Professionals who want to gain Hands-on..