Understanding Convolutional Neural Networks (CNN) Convolutional Neural Networks (CNN) are a type of feedforward neural network where artificial neurons can respond to a portion of the surrounding units within a coverage area, demonstrating outstanding performance in large image processing. CNN has five characteristics: 1. Local perception; 2. Parameter sharing; 3. Sampling; 4. Multiple convolutional kernels; … Read more
I am a master’s student at a double first-class university, and I am currently preparing for the 2024 autumn recruitment. While looking for internships in large model algorithm positions, I encountered many interesting interviews, so I decided to record these interview questions and share them with friends who, like me, are striving for a satisfactory … Read more
Convolutional Neural Networks and Recurrent Neural Networks are widely used in machine learning today. However, they are typically used for completely different use cases. What are the principles and differences of CNN and RNN in artificial intelligence? In machine learning, each type of artificial neural network is tailored for specific tasks. Below, we will introduce … Read more
Star ★TopPublic AccountLove you all♥ Author: Chuan Bai Translated by: 1+1=6 1 Introduction The financial market mainly deals with time series problems, and there are numerous algorithms and tools around time series forecasting. Today, we use CNN for regression-based prediction and compare it with some traditional algorithms to see how it performs. We focus on … Read more
Star ★TopPublic AccountLove you all♥ Author: Nayak Translated by: 1+1=6 0 Introduction This article is based on a research paper titled“Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach”: Get the paper at the end of the article We borrowed some core ideas from the authors of this paper while … Read more
The WeChat public account on quantitative investment and machine learning is a mainstream self-media in the industry focusing onquantitative investment, hedge funds,Fintech, artificial intelligence, big data and other fields.The public account has over300,000+ followers from industries such aspublic funds, private equity, securities, futures, banks, insurance, and universities, and it won the 2021 AMMA Excellent Brand … Read more
Reported by Machine Heart Machine Heart Editorial Department Researchers from ByteDance have proposed a next-generation visual Transformer, Next-ViT, which can be effectively deployed in real industrial scenarios. Next-ViT can infer quickly like a CNN while maintaining the powerful performance of a ViT. Due to the complex attention mechanisms and model designs, most existing visual Transformers … Read more
New Intelligence Report Source: Microsoft Editor: LRS, Xiao Yun [New Intelligence Guide] Microsoft has published a new paper on arxiv, bringing CNN into Transformer to simultaneously consider global and local information. In the development of computer vision technology, the most important model is the Convolutional Neural Network (CNN), which serves as the foundation for other … Read more
Machine Heart reports Editor: Rome Rome Video understanding faces immense challenges due to significant spatiotemporal redundancy and complex spatiotemporal dependencies. Overcoming these two issues is extremely difficult, and CNNs, Transformers, and Uniformers struggle to meet these demands. Mamba presents a promising approach; let’s explore how this article creates video understanding with VideoMamba. The core goal … Read more
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