Vadim Nelidov
Vadim Nelidov is a Lead Data Science consultant at Xebia Data with diverse data & research experience in a variety of industries from energy sector to skincare and agriculture. He also has a research background in decision making sciences as well as several publications in this domain. Throughout his years in the data world, Vadim has been combining advanced data science with practical insights to make data work with an impact for the world. He aspires to see far beyond what is on the surface and get to the essence of the problems.
Vadim is passionate about sharing his knowledge and insights, believing that Data literacy should not be a privilege of a few. And his goal is to be there to make this a reality. Making the intricacies of data science intelligible and uncovering the regularities hiding in the data is a major source of inspiration for Vadim. With this goal in mind, he combines his years of experience in consulting with his background in statistics, research and teaching to make this knowledge accessible to businesses and individuals in need.
Xebia Data
Session
From sensor data to epidemic outbreaks, particle dynamics to environmental monitoring, much of crucial real world data has temporal nature. Fundamental challenges facing data specialist dealing with time series include not only predicting the future values, but also determining when these values are alarming. Standard anomaly detection algorithms and common rule-based heuristics often fall short in addressing this problem effectively. In this talk, we will closely examine this domain, exploring its unique characteristics and challenges. You will learn to apply some of the most promising techniques for detecting time series anomalies as well as relevant scientific Python tools that can help you with it.