MLNLP(Machine Learning Algorithms and Natural Language Processing) community is a well-known natural language processing community both at home and abroad, covering NLP master’s and doctoral students, university teachers, and enterprise researchers. The vision of the community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, … Read more
Click the above“Beginner Learning Vision” to choose to add “star” or “pin” Valuable content delivered promptly From | Zhihu Author | Mars Girl Link | https://zhuanlan.zhihu.com/p/146453159 Recently, due to work needs, I had to deploy a PyTorch model to a C++ platform. The basic process mainly refers to the official teaching examples, during which I … Read more
1 Configuration Issues (1). For computers equipped with a GPU and a need for deep learning, set up a usable and clean deep learning environment. (2). Configure with Anaconda3 + CUDA10.0 + CuDNN + Pytorch1.2 + Pycharm. (3). Resolve the issue of not being able to use the torchvision library in Pytorch. 2 Setup Process … Read more
Click on “Beginner Learning Vision“, select to add “Star” or “Top“ Important content delivered first-hand Author | Jin Hui @ Zhihu (Authorized) Source | https://zhuanlan.zhihu.com/p/220403674 1. Visualization of Network Structure When training a neural network, in addition to observing the trend of the loss function with respect to steps or epochs to establish a basic … Read more
Author: Little Cola Demon King @ Zhihu (Authorized) Source: https://zhuanlan.zhihu.com/p/378822530 Editor: Jishi Platform This article summarizes how to choose the appropriate loss function for different application scenarios, compares the advantages and disadvantages of different loss functions, and provides relevant PyTorch code. Direct Results: Image excerpted from the end of this article Main Text: In both … Read more
Click the “Little White Learns Vision” above, and choose to add “Bookmark” or “Pin“ Important content delivered first Editor’s Recommendation This article explores logic gate networks aimed at machine learning tasks through learning combinations of logic gates. These networks consist of logic gates such as AND and XOR. To achieve effective training, this article proposes … Read more
Author: z.defying Reprinted from: Datawhale Table of Contents: 1 Specify GPU ID 2 View Model Layer Output Details 3 Gradient Clipping 4 Expand Dimensions of a Single Image 5 One-Hot Encoding 6 Prevent Out of Memory When Validating Model 7 Learning Rate Decay 8 Freeze Parameters of Certain Layers 9 Use Different Learning Rates for … Read more
Reprinted from | Xinzhiyuan Author | JinHui Source | https://zhuanlan.zhihu.com/p/220403674 1 『Visualization of Network Structure』 When training a neural network, in addition to observing the trend of the loss function with each step or epoch to establish a basic understanding of the network optimization, we can also use some additional visualization libraries to visualize our … Read more
MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP graduate students, university professors, 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 both domestically and internationally, especially for … Read more
Source: Deephub Imba This article is approximately 3200 words long and is recommended to be read in 7 minutes. This article will introduce gradient checkpointing, a technique that allows you to train larger models on the GPU at the cost of increased training time. We will implement it in PyTorch and train a classifier model. … Read more