Recurrent Neural Networks

Transform Your Recommender System with Temporal Graph Neural Networks

Introduction Recommender systems have revolutionized the way we discover new products, music, movies, and even potential romantic partners. They analyze users’ past interactions with items and provide personalized recommendations based on their preferences. However, traditional recommender systems face several challenges, such as sparsity, cold-start, and scalability. To overcome these limitations, researchers have been exploring the …

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Strategies for Addressing Vanishing and Exploding Gradients in Deep Neural Networks

Vanishing and exploding gradients are two common issues that can arise when training deep neural networks. These issues can occur when the gradients of the parameters with respect to the loss function either become very small or very large, which can make it difficult for the network to learn effectively. In this article, we will …

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