Recommender systems are used in various areas with commonly recognized examples, including playlist generators for video and music services, product recommenders for online stores and social media platforms, and open web content recommenders. Recommender systems have also been developed to explore research articles and experts, collaborators, and financial services.
Recommender Systems: An Applied Approach using Deep Learning
Instructor: Packt - Course Instructors
Included with
Recommended experience
What you'll learn
Learn about deep learning and recommender systems
Explore the mechanisms of deep learning-based approaches
Learn to implement a two-tower model and TensorFlow for recommender system
Skills you'll gain
Details to know
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September 2024
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There are 3 modules in this course
In this module, we will introduce you to the instructor, providing a brief overview of their background and teaching style. You will also get a comprehensive outline of the course, including the main topics and concepts that will be covered, setting the stage for your learning journey ahead.
What's included
2 videos1 reading
In this module, we will delve into the foundational aspects of deep learning as it pertains to recommender systems. You will gain insights into transitioning from machine learning to deep learning, deploying models for inference, and understanding the intricacies of neural and variational autoencoder collaborative filtering. Additionally, you will explore the pros and cons of deep learning models and assess their effectiveness in recommender systems.
What's included
11 videos
In this module, we will guide you through creating a project that develops an Amazon product recommendation system. You will learn to use TensorFlow Recommenders, implement the two-tower model, and visualize data with WordCloud. The lessons cover downloading necessary libraries, preparing and rating data, performing train-test splits, and building the model. Finally, we will evaluate model accuracy and generate product recommendations.
What's included
15 videos1 assignment
Instructor
Offered by
Recommended if you're interested in Software Development
University of Minnesota
Sungkyunkwan University
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.