This is a free event.
Hi, let's get together for a Meetup and go out for a few beers after!
First speaker: Anna Mandli
Anna is an applied mathematician from Eötvös Loránd University, Budapest. Anna works at Bosch in a technology development team on data mining topics, while she continues her Ph.D. studies at the Hungarian Institute for Computer Science and Control (SZTAKI).
Data Mining in the Electronic Manufacturing Bosch as a leading automotive electronics supplier puts emphasis on Industry 4.0 applications. This presentation will outline the results of a data mining project, which aimed to reduce the fall out rate of an electronic part manufactured by Bosch. Analysis of the archive manufacturing data helped to reveal factors contributing to defects and to select the most informative diagrams to be visualized in an application. During this work we faced many challenges: the data is unbalanced, inhomogeneous and the measurements are often noisy. Moreover, data mining modeling was used for scrap rate prediction. A data-driven system was designed which can warn the machine operators if a critical increase in failure rate is expected.
Second speaker: Sean Kross
Sean formerly worked in the Johns Hopkins Data Science Lab where he and his colleagues developed The Data Science Specialization on Coursera.org. Sean is the author of Mastering Software Development in R, Developing Data Products, and The Unix Workbench. You can find him on Twitter @seankross.
My colleges and I saw the demand for data scientists ballooning and we decided to do something about it. In this talk, I will explain how the Johns Hopkins Data Science Lab leveraged the latest statistical, computational, and open source methods in order to create over a million new data scientists.
Third speaker: Justin Bozonier
Justin is the author of Test-Driven Machine Learning (published by Packt) and Lead Data Scientist in GrubHub's Financial Planning & Analytics group. The founding data scientist of GrubHub's split testing efforts, his team runs the company's experiment analysis platform, develops experiments and models to tune larger business operations, and data mines experiments and operational data to look for new business opportunities and value existing programs.
Abstract: The Test-Driven Company
Imagine if you came into work tomorrow and knew how much money your new product improvement made for your company. Imagine if you could come up with some crazy idea and prove it worked through rigorous experimentation. It's rare to work someplace that is that experiment-driven but we've achieved that at GrubHub. We'll review how experimentation started at GrubHub, how it grew to where it is today, and some lessons learned. By the time we're done, you'll wonder why anyone would do it any other way.