Recommendation engines are valuable assets for many services that we use in our daily lives. They play a vital role in many industries ranging from retail, e-commerce, entertainment, and even food delivery, while greatly uplifting the user experience. In this course, Build a Rating Recommendation Engine with Collaborative Filtering, you’ll acquire the skills to build your very own recommender system. First, you’ll be introduced to recommender systems, see the different types of recommender systems, and go into more detail on the particular technique that you’re going to use during this course – collaborative filtering. Next, you’ll discover how to build a recommender system using memory-based collaborative filtering. Finally, you’ll learn all about model-based collaborative filtering and gain the knowledge to code it up using Python. When you’re finished with this course, you’ll have the knowledge and skills to build your very own recommendation system.
Author Name: Pratheerth Padman
Author Description:
Pratheerth is a Data Scientist who has entered the field after an eclectic mix of educational and work experiences. He has a Bachelor’s in Engineering in Mechatronics from India, Masters in Engineering Management from Australia and then a couple of years of work experience as a Production Engineer in the Middle East. Then when the A.I bug bit him, he dropped everything to dedicate his life to the field. He is currently working on mentoring, course creation and freelancing as a Data Scientist.

Table of Contents

• Course Overview
  1min
• Getting Started with Recommender Systems
  17mins
• Memory-based Collaborative Filtering
  35mins
• Model-based Collaborative Filtering
  26mins