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Build a Rating Recommendation Engine with Collaborative Filtering

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Pratheerth Padman

1:20:36

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  • 1. Course Overview.mp4
    01:44
  • 1. Course and Module Overview.mp4
    01:27
  • 2. What Are Recommendation Systems.mp4
    03:09
  • 3. Content-based Filtering.mp4
    04:19
  • 4. Collaborative Filtering.mp4
    02:07
  • 5. Recommender Systems - Business Use Cases.mp4
    05:01
  • 6. Module Summary.mp4
    00:56
  • 1. Module Overview.mp4
    01:06
  • 2. Understanding Memory-based Collaborative Filtering.mp4
    04:06
  • 3. Demo - Setting up Your Environment.mp4
    02:50
  • 4. Demo - Dataset Introduction and Exploratory Data Analysis.mp4
    09:05
  • 5. Demo - User-based Collaborative Filtering.mp4
    08:38
  • 6. Demo - Item-based Collaborative Filtering.mp4
    08:53
  • 7. Module Summary.mp4
    00:43
  • 1. Module Overview.mp4
    00:53
  • 2. Understanding Model-based Collaborative Filtering.mp4
    09:00
  • 3. Demo - Movie Recommendations with SVD.mp4
    06:55
  • 4. Demo - Book Recommendations with Deep Learning.mp4
    08:36
  • 5. Module Summary and Feedback.mp4
    01:08
  • Description


    Recommendation systems pervade a great number of aspects of our daily lives. This course will teach you how to build your very own recommendation system using a technique called collaborative filtering.

    What You'll Learn?


      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.

    More details


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    Pratheerth Padman
    Pratheerth Padman
    Instructor's Courses
    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.
    Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.
    • language english
    • Training sessions 19
    • duration 1:20:36
    • level advanced
    • English subtitles has
    • Release Date 2023/03/30

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