JD NLP Enterprise Project Practical Training Camp Focusing on Cultivating the Top 10% NLP Engineers in the Industry Students interested in the course Add the course consultant’s WeChat Registration, course consultation 👇👇👇 01 Detailed Explanation of JD NLP Project Content △If you have questions about the course project content, you can watch this video 02 … Read more
Analyst Network of Machine Heart Analyst: Wu Jiying Editor:Joni Zhong As an important research topic in the fields of computer science and artificial intelligence, Natural Language Processing (NLP) has been extensively studied and discussed across various domains. With the deepening of research, some scholars have begun to explore whether there are connections between natural language … Read more
Reprinted with permission from Liu Zhiyuan’s Zhihu column Author: Liu Zhiyuan The author of this article, Liu Zhiyuan, is an associate professor in the Department of Computer Science and Technology at Tsinghua University. Professor Liu summarizes several common problems faced by researchers when writing NLP papers and has written this article. This article is not … Read more
Selected from GitHub Author:Sepehr Sameni Compiled by Machine Heart Contributors: Lu Word and sentence embeddings have become essential components of any deep learning-based natural language processing system. They encode words and sentences into dense fixed-length vectors, significantly enhancing the ability of neural networks to process textual data. Recently, Separius listed a series of recent papers … Read more
The knowledge graph is a very popular technology recently, integrating web crawling, natural language processing, machine learning, deep learning, graph databases, complex network analysis, and many other hot technologies into one. The technology density is high, making it a product that companies are very interested in, such as constructing semantic search, Q&A platforms, and intelligent … Read more
1. Introduction to Knowledge Graph A knowledge graph is a large-scale semantic network that provides a semantic representation of the real world. Entities are represented as nodes, while the properties of entities and the relationships between them are represented as edges, forming a web-like graph structure. This structured format is recognizable by humans and machine-friendly, … Read more
Knowledge graphs represent factual knowledge about the world through relationships between concepts, which are crucial for intelligent decision-making in enterprise applications. By encoding concepts and relationships as low-dimensional feature vectors, new knowledge can be inferred from existing facts in the knowledge graph. The most effective representation method for this task is called Knowledge Graph Embedding … Read more
Research Background In the era of big data and artificial intelligence, the position of literature as a core knowledge carrier has not changed. However, the current methods of literature resource management, such as information retrieval, databases, subject headings, and classification systems, cannot meet the higher-level needs of researchers. The knowledge graph is a novel mass … Read more
Authorized Reprint by Author Author: Li Wenzhe Excerpt from: Inclusive Big Data Center Introduction The Knowledge Graph is currently a hot research topic. Since Google launched its first version of the Knowledge Graph in 2012, it has sparked a wave of interest in both academia and industry. Major internet companies quickly launched their own Knowledge … Read more
Course Swift for TensorFlow Swift for TensorFlow combines the flexibility of Eager Execution with the high performance of graphs and sessions. Swift can analyze your Tensor code in the background and automatically build graphs. It also captures type errors and shape mismatches before running the code, allows input from any Python library, and features language-integrated … Read more