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
Source: Big Data Digest This article is about 2000 words long and is recommended for a 5-minute read. 800 images take only 2 minutes, and the program has been packaged. Recently, according to reports from Fudan University, Li Xiaokang, a PhD student from the School of Information Science and Engineering, used OCR and regular expressions … Read more
[New Friends] To know more serialized articles, please follow the blue text below the title “Zhenli Pai”, and check the historical messages. [Old Friends] Click the top right corner “…”, to forward or share this article with your friends. Background (Introduction) With the rapid development of computer networks, the electronicization of information has become an … Read more
Source: DeepHub IMBA This article is approximately 5400 words long and is recommended for a reading time of over 10 minutes. This article discusses 12 pain points encountered during the development of RAG pipelines (7 of which are sourced from papers, and 5 from our own summary), and proposes corresponding solutions to these pain points. … Read more
When discussing the differences between AI (Artificial Intelligence) and intelligence, it can be understood from several perspectives:Artificial Intelligence (AI) refers to the ability of computer systems to perform tasks that typically require human intelligence. This includes perception, reasoning, learning, problem-solving, etc. AI can learn and optimize through algorithms and big data, enabling it to perform … Read more