Graph-Powered Machine Learning and Chatbots with Neo4j and Amazon Alexa

This month we've got two talks the night before the GraphTour London event. This event is a co-hosted with friends in the community! Data Science Festival - London (https://www.meetup.com/Data-Science-Festival-London/)
Data Science with IoT Meetup (https://www.meetup.com/Data-Science-for-Internet-of-Things-Meetup-London/)
Skills Matter Meetup (https://www.meetup.com/skillsmatter)
London GraphDB Meetup (https://www.meetup.com/graphdb-london/)

It is kindly sponsored by GraphAware

Please sign up on the Skillsmatter page (https://skillsmatter.com/meetups/10647-graph-powered-machine-learning-and-chatbots-with-neo4j-and-amazon-alexa) so they know how many to expect

Graph-Powered Machine Learning
Alessandro Negro, Chief Scientist at GraphAware

Graph-based machine learning is becoming an important trend in Artificial Intelligence, transcending a lot of other techniques. Using graphs as basic representation of data for ML purposes has several advantages: (i) the data is already modeled for further analysis, explicitly representing connections and relationships between things and concepts; (ii) graphs can easily combine multiple sources into a single graph representation and learn over them, creating Knowledge Graphs; (iii) improving computation performances and quality. The talk will discuss these advantages and present applications in the context of recommendation engines and natural language processing.

Dr. Alessandro Negro (https://twitter.com/alessandronegro?lang=en) is Chief Scientist at GraphAware. He has been a long-time member of the graph community and is the main author of the first-ever recommendation engine based on Neo4j. At GraphAware, he specializes in recommendation engines, graph-aided search, and NLP.

Knowledge Graphs and Chatbots with Neo4j and Amazon Alexa
Christophe Willemsen, Principal Consultant at GraphAware

Knowledge Graphs are becoming the de-facto solution for managing complex aggregated knowledge, and Neo4j is the leading platform for storing and querying connected data. In this talk, Christophe will describe a graph-centric cognitive computing pipeline and detail the process from the ingestion of unstructured text up to the generation of a knowledge graph, queryable using natural language through chatbots built for Amazon Alexa.

Christophe Willemsen (https://twitter.com/ikwattro) is a Principal Consultant at GraphAware. He is a Neo4j expert and has been involved in many projects for recommendation engines and relevant search. He is now leading the development of the GraphAware Knowledge Platform, a graph-based cognitive solution for Enterprises.