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Recommendation system Real World Projects using Python

Name: Recommendation system Real World Projects using Python
Price: 19.99 USD
Availability: InStock

About this course

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 NetfixGoogle: Search resultsThats why Google is the most successful technology company today.YouTube: Video dashboardI’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 SystemPopularity-based Recommender SystemHybrid Model based on Average weighted & PopularityCollaborative filtering.Content based filteringand 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 LinkHow to make most from the course ?Check out the lecture "Utilize This Golden Oppurtunity  , QnA Section !"

63/100

CourseAsk score

What the provider tells you: 39/45
Who stands behind it: 8/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

understand use cases of recommender systems
implement average weighted and popularity-based recommendation techniques
apply hybrid models in recommendation systems
utilize collaborative and content-based filtering methods

Course objectives

to provide a thorough understanding of how recommender systems function
to equip students with hands-on experience through real-world projects

Machine Learning #python #machine learning #data analysis #recommender systems #content-based filtering #collaborative filtering #user behavior prediction #hybrid models #average weighted techniques #popularity-based recommendations

$19.99

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