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Claire Sullivan

0:36

What Is a Knowledge Graph

7:22

What Knowledge Graphs Are Useful for

9:14

Rdf Triples Resource Description Framework

11:14

Root of the Sentence

17:54

Querying the Google Knowledge Graph

28:57

Add Node Properties

30:58

Method 2 the Nlp Lite Approach

31:57

Nlp Cleaning

33:12

Text Cleaning

33:22

Machine Learning on Graphs

36:33

Random Walk around the Graph

40:38

Connection Details

49:30

Create Collab Notebooks

49:59

Create a Collab Notebook

50:10

Helper Functions

55:32

Node Labels

58:04

Cipher Queries

1:06:04

Match Node

1:09:56

Relationships

1:10:09

Solutions

1:13:01

Relation Type

1:15:05

Levenshtein Distance

1:17:58

Data Science Code

1:18:37

Basic Node Classification

1:22:13

Creating Node to Vect Embeddings

1:27:46

Open Notebook from Github

1:34:15

Populate that Graph

1:36:12

Import the Json

1:36:29

Pip Install the Neo4j Package

1:37:17

Can I Do Deep Learning on Graphs

1:51:03
Training Series: Create a Knowledge Graph: A Simple ML Approach
This talk will start with unstructured text and end with a knowledge graph in Neo4j using standard Python packages for Natural Language Processing. From there, we will explore what can be done with that knowledge graph using the tools available with the Graph Data Science Library. Useful links:

Follow along using the transcript.

Neo4j

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