Instructor-led (classroom)
Beginner
90 MINUTES
English
In this course, you’ll apply your knowledge of classification models and embedding to build a ML
pipeline that functions as a recommendation engine.
A 360-degree learning approach that you can adapt to your learning style
Engage and learn more with these live and highly-interactive classes alongside your peers
24/7 Teaching Assistance Keep engaged with integrated teaching
Projects provide you with sample work to show prospective employers.
Real-world projects relevant to what you’re learning throughout the program
A support team focused on helping you succeed alongside a peer community
In this module, we review the scope and plan for the course, define what recommendation
systems are, review the different types of recommendation systems and discuss common
problems that arise when developing recommendation systems.
Content-Based Recommendation Systems
In this module, we demonstrate how to build a recommendation system using
characteristics of the users and items.
COLLABORATIVE FILTERING RECOMMENDATION SYSTEMS
In this module, we show how the data of the interactions between users and items from
many different users can be combined to improve the quality of predictions.
Neural Networks for Recommendation Systems
In this module we show how various recommendation systems can be combined as part of
a hybrid approach.
Building an End-to-End Recommendation System
In this module we put all the pieces together to build a smart end-to-end workflow for
your newly built WALS recommendation model for news articles.
Summary
In this final module, we review what you have learnt so far about recommendation
systems and the specialization more broadly.
A Professional Machine Learning Engineer designs, builds, and productionizes ML models to solve business challenges using Google Cloud technologies and knowledge of proven ML models and techniques. The ML Engineer is proficient in all aspects of model architecture, data pipeline interaction, and metrics interpretation and needs familiarity with application development, infrastructure management, data engineering, and security.
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