MLNLP community is a well-known machine learning and natural language processing community in China and abroad, covering NLP master’s and doctoral students, university teachers, and corporate researchers. The Vision of the Community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning in China and abroad, … Read more
Click the above“Beginner’s Guide to Vision”, select to add “Bookmark” or “Pin” Heavyweight content delivered first-hand Source: Xinzhi Yuan [Guide] The latest 3D visualization tool ‘mm’ released by the Pytorch team can simulate matrix multiplication in a virtual world. The simulated world of matrices is truly here. Matrix multiplication (matmul) is a very important operation … Read more
Click on "Xiaobai Studies Vision" above, select to add "Star" or "Top" Heavy content, delivered first time For academic sharing only, does not represent the position of this public account. Contact for deletion if infringing. Reprinted from:Source | Jishi Platform Author | Jack Stark@Zhihu The best resource for PyTorch is the official documentation. This article … Read more
This article was compiled by a PhD student from Harbin Institute of Technology over the course of six months, consisting of a total of fourteen chapters. It starts with the basics of creating tensors and gradually deepens, covering almost all commonly used functions! [From Beginner to Pro in PyTorch, AI Deep Learning Neural Network Learning … Read more
“Standing on the shoulders of giants” — this is precisely the benefit that pre-trained models bring in deep learning. Training deep neural networks from scratch is both resource-intensive and time-consuming. However, the good news is that PyTorch’s pre-trained models can effectively solve this issue. PyTorch provides models that have learned robust features on large datasets, … Read more
Introduction When constructing models, especially when dealing with the input-output data formats between layers, some commonly used data processing functions such as tensor calculations and broadcasting mechanisms are very important. They remain indispensable when later using the Transformers library with pre-trained models. This article aims to explain the most commonly used Pytorch processing functions for … Read more
Source: Data Analysis and Applications 1 Introduction Our experience of the world is multimodal — we see objects, hear sounds, feel textures, smell odors, and taste flavors. A modality refers to the way something occurs or is experienced; when a research question involves multiple modalities, it has multimodal characteristics. For artificial intelligence to make progress … Read more
We have discussed computer vision (or more narrowly, machine vision) before. Last year, the cover story of Electronic Engineering Magazine also talked about computer vision, but the content at that time was more focused on how computers acquire and understand image information from the outside world, leaning towards the perception aspect. According to the definition … Read more
Editor’s Note In order to deepen the understanding of the relevant terms in the “Decision of the Central Committee of the Communist Party of China on Further Deepening Reform and Promoting Chinese-style Modernization” adopted at the 20th Central Committee’s Third Plenary Session among the vast number of party members and cadres, the Central Party School … Read more
Table of Contents What is GAN? What Can GAN Do? Framework and Training of GAN Similarities and Differences Between GAN and Other Generative Models Existing Problems of GAN Models (Continued from last issue) 3 Framework and Training of GAN Previously, we mentioned that GAN consists mainly of two parts: the generator model and the discriminator … Read more