Topic

Data Science

idalab goes PyData

This year’s PyData Berlin conference, taking place from July 6th to 8th at the Charité-Campus (Virchow), was a huge success and with almost 600 participants the biggest PyData conference all over Europe. Concerned with providing a forum for python users and developers in the field of data analysis, a wide range of topics was covered in four simultaneous tracks, going from deep learning and scalability over data privacy and best practices to putting machine learning into production.

idalab seminar #12: The data-privacy dilemma: How full homomorphic encryption could bring healthcare into the digital era

Imagine this: The key to better cancer treatments is within reach, based on patterns from data that is scattered across various locations all over the world. This data could be digitalised, labelled, collected, stored and interpreted. However, this data belongs to a countless number of individuals – and their right to data privacy weighs just as much as the dream of curing a lethal disease.

What do we mean by “data”?

Some technical terms are so ubiquitous and (apparently) unambigious, that they almost become a transparent fluid: always used but never much reflected upon. Interestingly enough, the word “data” 1 is such a term. It is an abstract, weightless and unidentified mass of numbers (mostly digitally encoded), with a potent influence on our lives. It is also considered a rich source of insight that is worth being tapped. But what are the origins of the word “data” – and what are its implications?

idalab seminar #11: SELECT * FROM … natural language: databases, we need to talk!

Do you know the feeling? All you want is a break-down of last year’s sales numbers and suddenly you find yourself typing tedious heaps of SQL-statements, clicking through complicated dashboards or looking for the right number in an Excel sheet. The vast majority of decision makers has better things to do with their time. That’s why business intelligence software was originally born. But only 20% of users are actually coping with the solutions BI software provides. Instead, the BI team is spammed with ad hoc data requests. What if everyone had a personal virtual data analyst at hand?

Der Mythos der Juristen: Für Standardisierung zu individuell – Interview mit Professor Breidenbach Teil II

Anlässlich der Veröffentlichung des „Rechtshandbuch Legal Tech“, erschienen im C.H. Beck Verlag, waren wir im Gespräch mit Professor Breidenbach. Ausgehend von seinem Buchkapitel „Industrialisierung des Rechts“ entwickelte sich eine lebhafte Diskussion zum „Möglichkeitsraum Legal Tech“. Im zweiten Teil des Interviews sprechen wir über die digitale Fertigungsstraße, darüber, was sich an der Ausbildung der Juristen ändern sollte, wie man durch Potenzialentfaltung an Schulen gegen die Spaltung der Gesellschaft vorgehen könnte, und die Frage, ob die Industrialisierung des Rechts den Juristen von seiner Arbeit entfremdet.

idalab seminar #10: Precision Medicine – How to Identify Biomarkers that Help Patients Choose Their Best Treatment Option

In idalab seminar #10, we turn to the field of Precision Medicine. Dr. Nicole Krämer from Staburo GmbH will give a talk on how Data Science can help physicians to predict a patient’s reaction to a certain treatment in advance.

Der Mythos der Juristen: Für Standardisierung zu individuell – Interview mit Professor Breidenbach Teil I

Anlässlich der Veröffentlichung des „Rechtshandbuch Legal Tech“, erschienen im C.H. Beck Verlag, waren wir im Gespräch mit Professor Breidenbach. Ausgehend von seinem Buchkapitel „Industrialisierung des Rechts“ entwickelte sich eine lebhafte Diskussion zum „Möglichkeitsraum Legal Tech“.

The idalab seminars: our contribution to the AI discussion

For a while now, starting in March 2016, you have received information about the idalab seminars via our newsletter, Twitter, Linkedin or our Blog. For those who have never heard, or never attended – and always wondered – we want to take a brief moment to present to you what idalab seminars are all about, where we want to go with them and how we’d like you to be involved.

How to achieve maximum office happiness: Turning the allocation of office seats into an integer programming problem

The allocation of office seats can be tackled with either elbows, consideration and compromise – or the skills of a Data Scientist. Naturally, at idalab, we treated finding the perfect seating order as a mathematical optimisation problem. We are quite proud of the result. May we present to you what we’re fondly calling: The Optimum Happiness Distribution Project.