Big Data Digest Production Source: Google Blog Compiled by: Mali The weather in spring can change faster than you can turn a page; one moment it’s sunny, the next moment there’s a raging storm. In fact, accurately predicting the weather weeks or even minutes in advance is a scientific challenge that has a broad impact … Read more
“Programming is the art of telling another human being what one wants the computer to do.” — Donald Knuth 📑Paper:A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond 🔧GitHub:https://github.com/QiushiSun/NCISurvey Note: The authors of the paper are from Shanghai Artificial Intelligence Laboratory, The University of Hong Kong, National University of Singapore, East China Normal University, … Read more
Over 200 star enterprises and 20 top investors from renowned investment institutions participated! “New Intelligence Growth List” aims to discover innovative companies in the AI field with “tenfold growth in three years“, will the next wave of AI unicorns include you? Click read the original text for details! According to Lei Feng Network: Artificial intelligence … Read more
Introduction: Hello, readers of the “Beginner’s Data Learning” series! It has been a while. Google recently launched a neural network visualization teaching platform called “TensorFlow Playground”. You can now play with neural networks right in your browser! Isn’t that amazing? After trying it out with the beginner, you’ll definitely feel like, “Aha, this is what … Read more
1 Introduction Deep neural networks are composed of neurons organized into layers and interconnected, capturing their architecture through computation graphs, where neurons are represented as nodes and directed edges connect different layers of neurons. The performance of neural networks depends on their architecture, but there is currently a lack of systematic understanding of the relationship … Read more
Big Data Digest authorized reprint from AI Technology Review Authors: Li Mei, Huang Nan Editor: Chen Caixian In the past decade, deep learning has achieved remarkable victories, with methods using large parameters and data through stochastic gradient descent proven effective. The gradient descent typically uses the backpropagation algorithm, which has led to ongoing questions about … Read more
Produced by Big Data Digest Compiled by: Andy The backpropagation algorithm belongs to deep learning and plays an important role in solving model optimization problems. This algorithm was proposed by Geoffrey Hinton, known as the father of deep learning. In 1986, he published a paper titled “Learning representations by back-propagating errors” (Rumelhart, Hinton & Williams, … Read more
In the field of deep learning, there are many specialized terms that can be quite overwhelming at first glance. However, as we delve deeper, we gradually start to understand them, albeit feeling like something is still missing. Today, we will discuss a specialized term called Attention mechanism! 1. Intuitive Understanding of Attention Imagine a scenario … Read more
Click the above“Machine Learning and Generative Adversarial Networks” to follow and star Get interesting and fun cutting-edge content! Author on Zhihu: Mr. Good Good, please delete if infringing https://zhuanlan.zhihu.com/p/361893386 1 Background Knowledge The Attention mechanism was first proposed in the field of visual images, probably in the 1990s, but it really gained popularity with the … Read more
Produced by Machine Learning Algorithms and Natural Language Processing @Official Account Original Column Author Don.hub Position | Algorithm Engineer at JD.com School | Imperial College London Outline Intuition Analysis Pros Cons From Seq2Seq To Attention Model Seq2Seq is important, but its flaws are obvious Attention was born Write the encoder and decoder model Taxonomy of … Read more