Machine Learning and Statistical Methods for Time Series Analysis

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In this talk, Steve and Tom will present a deep algorithmic dive into the new machine learning technologies available in the Elastic Stack and how they can be applied to real datasets.

Specifically, they will focus on some of the unsupervised machine learning techniques Elastic uses, and the challenges and constraints which exist in order to provide operationally useful insight when applying these technologies to real time series data.

Steve Dodson

Dr. Steve Dodson is Tech Lead, Machine Learning at Elastic. He was previously founder and CTO at Prelert (acquired by Elastic in Sept 2016). Steve has over 18 years of experience in enterprise systems and software development, focused on large distributed systems, complex event processing and machine learning. Prior to software development, Steve worked in the Computational Mechanics group at Imperial College, London where he delivered key contributions to the field, resolving scalability issues using a novel approach to solving Maxwell's equations which allowed it to become a practical technique used today by major companies.

Tom Veasey

Tom Veasey joined Elastic in September 2016. He is a member of the machine learning team. He started out as a data scientist working on satellite, radar, and drug discovery projects, and had detours into EDA and FX derivatives pricing. He has a Masters in Physics from the University of Cambridge.