Data Science Foundations: Knowledge Graphs

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Daniel Burgwinkel

31:12

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[1] Introduction

[1] Knowledge graphs in corporate use.mp4

01:53

[2] 1. What Are Knowledge Graphs

[1] Knowledge graphs in use by digital companies.mp4

02:01

[2] Google Knowledge Graph.mp4

03:42

[3] Knowledge graphs in media and ecommerce.mp4

02:32

[4] What is a knowledge graph.mp4

02:29

[3] 2. Use Cases for Knowledge Graphs

[1] Knowledge management.mp4

01:10

[2] Recommender engines.mp4

00:27

[3] Machine learning with knowledge graphs.mp4

01:14

[4] 3. Industry-Specific Knowledge Graphs

[1] Knowledge graphs in healthcare.mp4

01:23

[2] Sector-specific knowledge models.mp4

01:17

[3] Text mining and machine learning.mp4

01:09

[5] 4. Recommendations for Implementation

[1] Benefits of knowledge graphs in digital transformation.mp4

02:19

[2] Checklist for the use of knowledge graphs in an organization.mp4

02:40

[3] Create use-case ideas for knowledge graphs.mp4

01:38

[6] 5. How to Build a Knowledge Base

[1] Create a taxonomy or data catalog.mp4

01:14

[2] Create an ontology.mp4

01:59

[3] Build the knowledge base.mp4

01:15

[4] Make knowledge usable internally and externally.mp4

00:15

[7] Conclusion

[1] Further information.mp4

00:35

Description

The term “knowledge graph” describes a semantic search based on the systematic compilation and processing of data and was first coined by Google. Leading internet companies have been using knowledge graphs for several years to present information that is tailored to customers’ needs. You can also use knowledge graphs to map your company’s internal knowledge and improve search results. Knowledge graphs can also improve the results of AI or machine learning systems. In this course, blockchain technology leader Daniel Burgwinkel explains what knowledge graphs are, offers examples and use cases, gives you practical recommendations on how to implement knowledge graphs, and shows you how to build a knowledge base. This course is aimed at data stewards, digital transformation managers, and data scientists who are responsible for data stocks and knowledge management.

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Data Science

Daniel Burgwinkel

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Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.