Data Science Workshop, EPFL, June 4-6th

What do Swisscom, Expedia, Cisco, Google, Frontiers and Bühler have in common?

They will present use cases at the Data Science Workshop, EPFL, June 4-6th.

Industry Talks

The 2018 IEEE Data Science Workshop is a new workshop that aims to bring together researchers in academia and industry to share the most recent and exciting advances in data science theory and applications. In particular, the event will gather researchers and practitioners in various academic disciplines of data science, including signal processing, statistics, machine learning, data mining and computer science, along with experts in academic and industrial domains, such as personalized health and medicine, earth and environmental science, applied physics, finance and economics, intelligent manufacturing. 

The industrial audience will particularly value workshops geared toward their daily analytics challenges, as well as sessions focusing on IoT and AI applications in an industrial environment.  Case studies will provide an in depth look on how data science can help solve tangible problems encountered by corporations.

Share

Data Analytics for Internal Audit

This is a guest post from Marcel Baumgartner, Data Analytics Expert at Nestlé S.A.

Introduction

Large publicly listed companies not only have external auditors who check the books, but often also a large community of internal auditors. These collaborators provide the company with a sufficient level of assurance in terms of adherence to internal and external rules and guidelines. This covers financial… Continue reading...

Share

The academic tip: What is Deep Learning?

This is a guest post from Jacques Zuber, Data Science Teacher at HEIG-VD.

The commonly called deep learning or hierarchical learning is now a popular trend in machine learning. Recently during the Swiss Analytics Meeting Prof. Dr. Sven F. Crone presented how we can use deep learning in the industry in a forecasting perspective (beer forecasting for manufacturing, lettuce forecasting in… Continue reading...

Share

Interview of Jerome Berthier, Head of BI and Big Data at ELCA

Data Mining Research (DMR): Can you tell us who you are and how you came to the field of Data Science?

Jerome Berthier (JB): My name is Jerome Berthier, I am an engineer in Computer Science and I have an MBA in management. After 10 years working in different roles for an IT provider (developer, sales representative, managing director), I joined… Continue reading...

Share

Will Data Scientists be Replaced by Machines?

Data Science automation is a hot topic recently, with several articles about it[1]. Most of them discuss the so-called “automation” tools[2]. Too often, editors claim that their tools can automate the Data Science process. This provides the feeling that combining these tools with a Big Data architecture can solve any business problems.

The misconception comes from the confusion between the whole Data Science process… Continue reading...

Share

Data Science Book Review: Statistics Done Wrong

If you read this blog, you are very likely to be involved in any kind of data collection, manipulation or analysis. When not performed wisely, your analysis will lead you to incorrect conclusions. Alex Reinhart, in his book Statistics Done Wrong, has listed several concepts that are key when analysing data, such as statistical power, correlation/causation and publication bias.
Share