Recommender Systems Complete Course Beginner to Advanced
Master recommender systems: Learn machine learning and deep learning approaches for building recommendation engines.
Master recommender systems: Learn machine learning and deep learning approaches for building recommendation engines.
This comprehensive course covers recommender systems from fundamentals to advanced implementations. Students learn both machine learning and deep learning approaches, starting with basic concepts and progressing to sophisticated techniques. The curriculum includes content-based filtering, collaborative filtering, and neural network-based recommendations. Through hands-on projects using TensorFlow, learners implement real-world recommendation systems including song recommendations and Amazon product recommendations.
Instructors:
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What you'll learn
Understand different types of recommender systems
Implement content-based and collaborative filtering
Master deep learning approaches for recommendations
Build real-world recommendation systems
Use TensorFlow for neural network-based recommendations
Develop practical skills through hands-on projects
Skills you'll gain
This course includes:
492 Minutes PreRecorded video
1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 3 modules in this course
This course provides a comprehensive exploration of recommender systems, covering both traditional machine learning and modern deep learning approaches. Students learn the fundamentals of recommendation systems, including content-based and collaborative filtering techniques. The curriculum progresses through machine learning methods to advanced deep learning implementations using TensorFlow. Through practical projects, learners develop skills in building recommendation engines for various applications like music, movies, and product recommendations.
Introduction
Module 1 · 18 Minutes to complete
Recommender Systems with Machine Learning
Module 2 · 6 Hours to complete
Deep Learning for Recommender Systems: An Applied Approach
Module 3 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Enhancing IT Education Through Expert-Led Learning
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