Stanford CS231N Deep Learning and Computer Vision: Optimization and Stochastic Gradient Descent

Stanford CS231N Deep Learning and Computer Vision: Optimization and Stochastic Gradient Descent

This article is a translated note of the Stanford University CS231N course, authorized for translation and publication by Professor Andrej Karpathy of Stanford University. The Big Data Digest work is prohibited from being reproduced without authorization; specific requirements for reproduction can be found at the end of the article. Registration is open! Machine Learning training … Read more

Discussing the Gradient Vanishing/Explosion Problem in RNNs

Discussing the Gradient Vanishing/Explosion Problem in RNNs

Follow the public account “ML_NLP“ Set as “Starred“, delivering heavyweight content to you first! Reprinted from | PaperWeekly ©PaperWeekly Original · Author|Su Jianlin Unit|Zhuiyi Technology Research Direction|NLP, Neural Networks Although Transformer models have conquered most fields in NLP, RNN models like LSTM and GRU still hold unique value in certain scenarios, making it worthwhile for … Read more