5

9 - Building an ML Pipeline in Neo4j Link Prediction Deep Dive

 3 years ago
source link: https://www.youtube.com/watch?v=qdbhCG-Yn74
Go to the source link to view the article. You can view the picture content, updated content and better typesetting reading experience. If the link is broken, please click the button below to view the snapshot at that time.
neoserver,ios ssh client
0:00 / 33:57

9 - Building an ML Pipeline in Neo4j Link Prediction Deep Dive

61 views
Jul 8, 2021

29.4K subscribers

Building an ML Pipeline in Neo4j: Link Prediction Deep Dive Hands on deep dive into building a link prediction model in Neo4j, not just covering the marketing highlights but also all the tricky technical bits that make the difference between a great model and nonsense.

Alicia M. Frame Director of Data Science, Neo4j

Alicia Frame is the Director of Graph Data Science at Neo4j.

Jacob Sznajdman Graph Analytics Engineer, Neo4j

Jacob Sznajdman is an algorithm developer for Neo4j and the Graph Data Science library. He has experience in Machine Learning and Data Science from text classification, machine learning library building, query resource prediction and data-driven load balancing. He also holds a PhD in mathematics and has done research on the intersection of graph algorithms and machine learning.

Show lessShow more

0 Comments

Sort by
default-user=s48-c-k-c0x00ffffff-no-rj
Add a public comment...

Recommend

About Joyk


Aggregate valuable and interesting links.
Joyk means Joy of geeK