Classe_2E

This podcast explores how graph databases and artificial intelligence can be combined to create intelligent medical chatbots that assist with healthcare information and decision support. It discusses knowledge graphs, symptom-to-condition relationships, conversational AI, and the role of connected data in improving healthcare accessibility and patient engagement. Perfect for healthcare innovators, AI researchers, data scientists, and developers interested in the future of digital health solutions.

Every class has its own rhythm, stories, and shared experiences that shape the students within it. In this episode, we explore the everyday life, challenges, and moments that define Classe_2E. Discover how learning extends beyond textbooks into friendships and personal growth.

This podcast serves as the opening session of NODES 2022, introducing attendees to the event’s vision, agenda, and key themes surrounding graph technology. It highlights innovations in graph databases, knowledge graphs, data science, artificial intelligence, and connected data applications across industries. Perfect for developers, data professionals, business leaders, and anyone interested in the latest advancements in graph technology.

This podcast explores how graph databases help consumer product companies better understand customers, products, and market relationships. It discusses use cases such as recommendation engines, customer journey analysis, supply chain visibility, and product intelligence powered by connected data. Perfect for product managers, data professionals, business leaders, and developers seeking to leverage graph technology for consumer-focused innovation.

This podcast explores how graph databases and network analysis can be used to map and analyze the complex relationships between characters in the classic Chinese novel Romance of the Three Kingdoms. It discusses character networks, influence patterns, alliances, rivalries, and how graph technology reveals insights that may be difficult to identify through traditional literary analysis. Perfect for literature enthusiasts, historians, data scientists, and anyone interested in applying modern analytics to classic works.

This podcast explores how developers can rapidly build and deploy interactive data applications using Streamlit and Neo4j. It discusses rapid prototyping techniques, graph data visualization, user interface development, and best practices for transforming graph data into powerful, user-friendly applications. Perfect for Python developers, data scientists, and software engineers looking to accelerate application development with modern tools.