Fraud detection using machine learning & deep learning (Rubén Martínez) CyberCamp 2016 (English)

preview_player
Показать описание
Conference: Fraud detection using machine learning & deep learning

The goal of this presentation is to go over several Machine Learning and Deep Learning techniques so as to detect fraud.
Some of the algorithms and technologies that we intend to explain are, for instance, graphs, Neo4J, Apache Spark or Deep Learning libraries such as H2O.

Rubén Martínez Sánchez: Computer Engineer by UPM and Master in Data Science. I have developed courses such as the title of Project Development with UML and Java also taught by UPM, CEH, Intel vPro, Cloudera Developer Training for Apache Hadoop, Cloudera Developer Training for Apache Spark, Introduction to Big Data with Apache Spark (Databricks) or Principles of Functional Programming in Scala among others. I have worked as a security auditor in StackOverflow as well as professor of the Postgraduate in Computer Security and Systems Hacking in the Polytechnic University School of Mataró or the online superior title of Computer Security and Hacking Systems Ethics of the Rey Juan Carlos University. I have also participated as a co-author of Ra-Ma publishing houses such as Hacking and Web Page Security (MundoHacker), Hacking and Internet Security Ed. 2011, etc.
I am currently working on intelligent chatbots using Deep Learning.

CyberCamp is the major cybersecurity event that INCIBE organises on a yearly basis for the purpose of identifying, appealing, managing and contributing to the creation of talent in cybersecurity that can be transferred to the private sector according to its demands. This initiative is one of the tasks that the Trust in the Digital Sphere Plan, included in the Spain’s Digital Agenda, has requested INCIBE to carry out.

LEÓN - 2016 DECEMBER 1st, 2nd, 3rd and 4th.
Рекомендации по теме
Комментарии
Автор

Hola!
Podrías compartir el código. No se ve muy bien en el vídeo. Ciertamente me ha parecido muy interesante tu presentación. Gracias.

perevales