Click the “Expert Knowledge” above to follow and get professional AI knowledge! ▌Introduction The traditional Vector Space Model (VSM) assumes that feature items are independent of each other, which does not align with reality. To address this issue, a distributed representation of text (e.g., in the form of word embeddings) can be employed, representing text … Read more
Machine Heart reports Machine Heart Editorial Department In the field of computer vision, Convolutional Neural Networks (CNNs) have always been dominant. However, researchers are continuously attempting to apply Transformers from the NLP domain to cross-disciplinary studies, with some achieving quite impressive results. Recently, an anonymous ICLR 2021 submission paper directly applied the standard Transformer to … Read more
Machine Heart Column This column is produced by the Machine Heart SOTA! Model Resource Station, updated weekly on the Machine Heart public account every Sunday. This column will review common tasks in the fields of natural language processing and computer vision, and detail the classic models that have achieved SOTA on these tasks. You can … Read more
This article is a note from Andrew Ng’s DeepLearning.ai course, covering the content of neural networks. The previous part can be found in[Simple Explanation of Neural Networks Part One] 4Activation Function When building a neural network, one important question to consider is which activation function to use for each independent layer. In logistic regression, the … Read more
Click the “Expert Knowledge” above to follow for more AI insights! Source: Zhihu – Qs.Zhang https://zhuanlan.zhihu.com/p/30074544 【Introduction】Hello everyone, my name is Zhang Quanshi, a postdoctoral researcher at UCLA. Currently, I lead a team in Professor Zhu Songchun’s lab, focusing on explainable AI. The title of this article is quite grand; in this short essay, I … Read more
Ali Sister’s Guide: BERT, a landmark in the field of natural language processing, did not appear out of nowhere; it has its development principles behind it. Today, the Ant Financial Wealth Dialogue Algorithm Team has organized and compared the development history of deep learning models in the field of natural language processing. From simple neurons … Read more
Follow the official account “ML_NLP“ Set as “Starred“, heavy content delivered first time! As a major part of deep learning, model architecture has always been a hot topic of research. Besides AutoML technology, what are some unconventional and innovative network architectures? 1 Author: Yan You San Source: https://www.zhihu.com/question/337470480/answer/766380855This article has been authorized for reprint by … Read more
[Image] Convolutional Neural Networks (CNN), one of the classic forms of deep learning neural networks, is named for its computation process that includes convolution operations. CNNs extract local features from image data using convolutional layers, followed by pooling layers (Pooling Lay…
Brothers, today we are going to talk about a particularly “high-end” but actually very practical and interesting technology – Convolutional Neural Networks (CNN). Don’t be afraid, the name sounds quite intimidating, but actually, if we chat in plain language, you will find that, hey, this thing is not that difficult! First, we need to understand … Read more
Recently, researchers from Nanyang Technological University published a paper that describes the mathematical principles of convolutional networks. This paper explains the operations and propagation processes of convolutional networks from a mathematical perspective. It is very helpful for understanding the mathematical essence of convolutional networks and aids readers in implementing convolutional networks “from scratch” (without using … Read more