All current Knowledge Graphs Courses courses in 2024

12 Courses

Knowledge Graphs for RAG

Knowledge Graphs for RAG Knowledge graphs are instrumental in structuring complex data relationships, enabling intelligent search functionality, and developing robust AI applications capable of reasoning over various data types. They can integrate data from both structured and unstructured sources, including databases and documents, provi.
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RAG and Fine-Tuning Explained

RAG and Fine-Tuning Explained | LinkedIn Learning Unlock the power of AI with our in-depth course on Retrieval Augmented Generation (RAG) and fine-tuning, offered by LinkedIn Learning. This course breaks down these advanced concepts to help you build robust enterprise applications. Perfect for those interested in artificial int.
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AI TIME 如何迈向知识驱动的人工智能 ?

Join this enlightening lecture in Chinese to delve into the transformation towards knowledge-driven artificial intelligence. Discover how AI systems can enhance their capabilities by leveraging structured knowledge and reasoning, moving beyond traditional data-driven methods. University: Not specified Provider: XuetangX Categories: Arti.
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人工智能教育应用

人工智能被视为继蒸汽机、电力、互联网之后最有可能带来新的产业革命浪潮的技术,而教育领域则是人工智能技术影响最为深刻的领域之一。无论你是在校学生还是一线教师,只要对人工智能和教育感兴趣,都可以来学习这门课程。这门课程将介绍人工智能的核心技术与教育创新应用场景,帮助你深刻认识人工智能对教育体系的变革与推动作用,以及未来人工智能在教育领域的发展趋势.
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基于图神经网络的事实验证

加入这场由XuetangX提供的中文讲座,探索如何利用图神经网络进行有效的事实验证。该课程专注于图形深度学习方法的应用,以自动化执行事实检查和验证的任务。参与者将有机会学习如何构建知识图谱、实现图神经网络架构,并通过分析结构化知识库中的实体与证据之间的关系来判定主张的准确性。 该课程特别适合对深度学习、神经网络和知识图谱领域感兴趣的学习者,希望深入.
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从入门到大神:疫情知识智能服务核心技术实践

知识疫图-全球新冠疫情智能驾驶舱,是一个基于知识的全球新冠疫情风险评估和复工辅助决策系统,提供基于知识驱动、全球疫情统计数据和预测模型对世界各地的疫情发展及风险状况进行量化评估和预测(Forecasting); 跟踪(Tracing)最新各方面疫情进展,包括科学研究、政府动态和社会舆论等各方面; 面向地区、机构和个体提供复工复产(Recovering)各方面的辅助决策支持,包括地区.
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AI TIME:知识图谱的高效构建与工业应用

Discover innovative techniques for knowledge graph construction and apply them in industrial settings with the AI TIME course by XuetangX. Enroll now to deepen your understanding of knowledge graphs alongside related fields such as Artificial Intelligence, Graph Theory, and Data Integration.
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人工智能(通识课)

人工智能在互联网时代获得了前所未有的发展机遇,已经成为目前发展最迅速、对社会影响最大的新兴学科。由于人工智能是模拟人类智能解决问题的方法,几乎在所有领域都具有非常广泛的应用,所以,目前许多高校开设了大学生人工智能通识课程。 课程涵盖了人工智能的概念、发展简史、研究内容及应用,引导学生深入各个研究领域,并介绍知识表示、推理方法、搜索策略、遗传算.
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人工智能技术与应用

This course is tailored for engineering management graduate students, integrating artificial intelligence theory, experiments, and engineering practice. Theoretical topics include an introduction to AI, knowledge representation and graphs, search strategies, genetic algorithms, swarm intelligence, neural networks, machine learning, deep learni.
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知识图谱导论

课程背景 知识图谱的发展历史包括经典人工智能的核心命题及现代应用。 涉及知识表示、机器学习等多领域技术的综合运用。 不断融合如图神经网络、联邦学习的新兴技术。 课程目标 介绍知识图谱的基础知识,涵盖表示、存储、获取等多方面内容。 前沿领域如多模态知识图谱、知识增强的语言预训练包含在课程中。 培养系统性思维,拓展研究视野与.
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All upcoming courses at Knowledge Graphs Courses on the AI ​​Education website. Check out all courses Knowledge Graphs Courses and choose the one that's right for you.