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
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: Shijin Tian, Ni Ni, Hu Jia, Yun Zhou In many machine learning labs, machines have undergone thousands of hours of training. During this process, researchers often take many detours and fix many bugs, but it is certain that the experience and knowledge gained during the research process are … Read more
Reported by New Intelligence Editor: LRS [New Intelligence Overview] It has almost become a consensus that bigger neural networks are better, but this idea contradicts traditional function fitting theory. Recently, researchers from Microsoft published a paper at NeurIPS proving the necessity of large-scale neural networks mathematically, suggesting they should be even larger than expected. As … 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
Produced by Big Data Digest Authors:Ning Jing, Wei Zimin Have you ever thought about moving neural networks from computers into a piece of glass? Using neural networks for image recognition and intelligent recommendations has become very common. In recent years, the increase in computing power and parallel processing has made it a very practical technology. … Read more
Produced by Big Data Digest Source: eisenjulian Compiled by: Zhou Jiale, Qian Tianpei Using deep learning libraries like TensorFlow and PyTorch to write a neural network is no longer a novelty. But do you know how to elegantly build a neural network using Python and NumPy? Nowadays, there are many deep learning frameworks available, equipped … Read more