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Thursday, September 20 • 5:10pm - 5:25pm
Machine Learning Algorithms in Neo4j

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With user-defined procedures there is unlimited potential for analysis of graph data in Neo4j.
As you move from relational to graph database, you need not leave your most trusted statistical methods behind. Linear and logistic regression can be implemented with updating formulas so that the data and design of the model is as flexible as the graph database itself. We will demonstrate that a price predictor, built with linear regression, is a seamless addition to a graph database that contains short term housing rental data from Austin, TX.

avatar for Lauren Shin

Lauren Shin

Developer Relations, Neo4j
Lauren is excited to help facilitate the graph developer community as a student intern at Neo4j. Her studies at UC Berkeley lie in the intersection between math and computer science and she is passionate about increasing the accessibility of technical knowledge to all learners. The... Read More →

Thursday September 20, 2018 5:10pm - 5:25pm EDT
6. Wilder
  Neo4j Session, AI and Machine Learning
  • TAGS AI and Machine Learning
  • SLUG machine-learning-algorithms-in-neo4j