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blog.reachsumit.com | ||
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distill.pub
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| | | | | What components are needed for building learning algorithms that leverage the structure and properties of graphs? | |
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d2l.ai
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| | | | | [AI summary] This chapter provides an in-depth exploration of recommender systems, covering fundamental concepts and advanced techniques. It begins with an overview of collaborative filtering and the distinction between explicit and implicit feedback. The chapter then delves into various recommendation tasks and their evaluation methods. It introduces the MovieLens dataset as a practical example for building recommendation models. Subsequent sections discuss matrix factorization, AutoRec using autoencoders, personalized ranking with Bayesian personalized ranking and hinge loss, neural collaborative filtering, sequence-aware recommenders, feature-rich models, and deep factorization machines like DeepFM. The chapter concludes with implementation details and ev... | |
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memgraph.com
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| | | | | Find out what node embeddings are, how to generate them and where they can be used | |
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ben.bolte.cc
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| | | A quick introduction to using Theano for deep learning, from the bare-bones to a full neural network. | ||
