Descriptions
Recommender Systems Specialization, A Recommender System is a process that seeks to predict user preferences. This Specialization covers all the fundamental techniques in recommender systems, from non-personalized and project-association recommenders through content-based and collaborative filtering techniques, as well as advanced topics like matrix factorization, hybrid machine learning methods for recommender systems, and dimension reduction techniques for the user-product preference space. This Specialization is designed to serve both the data mining expert who would want to implement techniques like collaborative filtering in their job, as well as the data literate marketing professional, who would want to gain more familiarity with these topics. The courses offer interactive, spreadsheet-based exercises to master different algorithms, along with an honors track where you can go into greater depth using the LensKit open source toolkit. By the end of this Specialization, you’ll be able to implement as well as evaluate recommender systems. The Capstone Project brings together the course material with a realistic recommender design and analysis project.
What you’ll learn
- Build recommendation systems
- Implement collaborative filtering
- Master spreadsheet based tools
- Use project-association recommenders
Specificatoin of Recommender Systems Specialization
- Publisher : Coursera
- Teacher : Packt – Course Instructors
- Language: English
- Level : All Levels
- Lectures : 4
- Duration : 4 weeks to complete at 10 hours a week
Content of Recommender Systems Specialization
Pictures
Sample Clip
Installation Guide
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Subtitle : English
Quality: 720p
Download Links
Downloadly
Course 1 – Recommender Systems with Machine Learning
Course 2 – Recommender Systems Complete Course Beginner to Advanced
Course 3 – Recommender Systems: An Applied Approach using Deep Learning
Course 4 – Building Recommender Systems with Machine Learning and AI
Rapidgator
Course 1 – Recommender Systems with Machine Learning
Course 2 – Recommender Systems Complete Course Beginner to Advanced
Course 3 – Recommender Systems: An Applied Approach using Deep Learning
Course 4 – Building Recommender Systems with Machine Learning and AI
Password file(s): www.downloadly.ir
File size
4.46 GB
