Power personalized experiences. Build recommenders using collaborative filtering, content-based methods, and modern neural approaches.
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Basic algebra and statistics helpful but not required
Any programming experience; Python preferred
Follow these courses in order to complete the learning path. Click on any course to enroll.
This course teaches how to apply knowledge of classification models and embeddings to build a machine learning pipeline that functions as a recommendation engine using TensorFlow on Google Cloud Platform.
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Power personalized experiences. Build recommenders using collaborative filtering, content-based methods, and modern neural approaches.
You'll work through Understand core concepts and foundations; Build your first projects with guided tutorials; Gain confidence with hands-on exercises; Build and train machine learning models from scratch; Understand supervised, unsupervised, and reinforcement learning paradigms; Evaluate model performance using industry-standard metrics.
It's pitched at beginner level — a solid starting point if you're new to the topic.
1 curated course, sequenced from foundational to advanced.
Around $49 total if you buy every course — but many include free audit options.
Enroll in this path to track your progress and stay motivated.