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www.chrisritchie.org | ||
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cprimozic.net
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| | | | | Introduces a browser-based sandbox for building, training, visualizing, and experimenting with neural networks. Includes background information on the tool, usage information, technical implementation details, and a collection of observations and findings from using it myself. | |
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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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stribny.name
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| | | | | Fields in Artificial Intelligence and what libraries to use to address them. | |
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bdtechtalks.com
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| | | Gradient descent is the main technique for training machine learning and deep learning models. Read all about it. | ||
