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Data Science Foundations: Knowledge Graphs Preview

Data Science Foundations: Knowledge Graphs

With Daniel Burgwinkel Liked by 531 users
Duration: 31m Skill level: Intermediate Released: 7/29/2021

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Course details

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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Meet the instructor

Learner reviews

4.6 out of 5

394 ratings
  • 5 star
    Current value: 279 71%
  • 4 star
    Current value: 81 21%
  • 3 star
    Current value: 21 5%
  • 2 star
    Current value: 8 2%
  • 1 star
    Current value: 5 1%
  • Jean Meunier-Pion Jean Meunier-Pion

    Jean Meunier-Pion

    PhD Student (Data / AI / Reliability) | CentraleSupélec | LGI

    3/5 October 15, 2024
    It is a good introductory course to knowledge graphs, dealing with why and how they are used in the industry. However, it is not a technical course and does not get you fully covered if you want to get your own knowledge graph in practice. Many examples are shown (which is much appreciated), but a lot of them rely on a paid third-party service and cannot be easily accessed on your own.
    Helpful · Report
  • Oscar Quintana Oscar Quintana

    Oscar Quintana

    Data & AI Practitioner @ Banco Bci | Economist

    4/5 October 11, 2024
    Quite superficial, but clear and concise.
    Helpful · Report
  • Max Laufeld Max Laufeld

    Max Laufeld

    On a break

    2/5 September 13, 2024
    A lot of McWords like "We want to use artificial intelligence, especially machine learning, to gain insights, but the results should be comprehensible to humans". As for the advertised "How to build a knowledge base" section - Quoting from video "Third step is to build a knowledge base and feed it with data. You can analyze large volumes of text documents with machine learning and map them to a knowledge graph" and then he shows a graph somebody else made. Could the instructor have made it easier for himself? I think not. I suggest you remove the intermediate labelling on this course.
    Helpful · Report

Contents

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