Click on the above “Mechanical and Electronic Engineering Technology” to follow us To build a neural network model based on PyTorch for predicting outputs, you can follow these steps: Define the Problem: First, clarify whether the problem is a regression problem or a classification problem. If the output is a continuous value, it may be … Read more
MLNLP(Machine Learning Algorithms and Natural Language Processing) community is a well-known natural language processing community both domestically and internationally, covering NLP graduate 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, especially for beginners. … Read more
MLNLP ( Machine Learning Algorithms and Natural Language Processing ) community is a well-known natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university teachers, and corporate researchers. The vision of the community is to promote communication between the academic and industrial fields of natural language processing and machine learning, … Read more
Author丨Jiefa Shouzhangsheng@Zhihu Link丨https://zhuanlan.zhihu.com/p/559887437 Using data augmentation techniques can increase the diversity of images in the dataset, thereby improving the model’s performance and generalization ability. The main image augmentation techniques include: Resizing Grayscale Transformation Normalization Random Rotation Center Cropping Random Cropping Gaussian Blur Brightness and Contrast Adjustment Horizontal Flip Vertical Flip Gaussian Noise Random Blocks Central … Read more
This article is approximately 1800 words long and is recommended to be read in 5 minutes. This article will deeply introduce the 7 core functions of the torch.utils.data module in PyTorch, which can help you better manage and manipulate data. In machine learning and deep learning projects, data processing is a crucial part. PyTorch, as … Read more
Abstract: Stakeholder financial risk is one of the most socially harmful risks in financial risks. Effectively identifying stakeholder financial risks and safeguarding financial security is the core of financial risk prevention. In the field of stakeholder financial risk prevention, information extraction from multi-source heterogeneous data and the combination of data models are crucial. This article … Read more
1. Data Processing The mini-batch data used for training RNNs differs from the usual data. This data should typically be arranged in a time series. For DI-engine, this processing is done during the collector phase. Users need to specify learn_unroll_len in the configuration file to ensure that the length of the sequence data matches the … Read more
Neural Network Models It’s that time of the week again! Today, Xiao Jun is sharing neural network models for everyone to learn together! Neural networks are complex network systems formed by a large number of simple processing units (called neurons) that are widely interconnected. They reflect many of the basic features of brain function and … Read more
As a programmer, we are accustomed to understanding the underlying principles of the tools and middleware we use. This article aims to help everyone understand the underlying mechanisms of AI models, making it easier for those without an AI background to learn or apply various large models. 1. The Relationship Between GPT and Neural Networks … Read more
Originally from Python Artificial Intelligence Frontier Graph Neural Networks are widely used in recommendation systems, knowledge graphs, and traffic road analysis due to their advantages in processing non-Euclidean space data and complex features. However, when the graph data volume increases, problems arise: computation becomes extremely slow, memory cannot hold it, and communication in distributed systems … Read more