When Microsoft presented their new project ELL, the Embedded Learning Library, to the public at the end of June 2017, the media echo failed to acknowledge its groundbreaking potential. Only a few tech-focused news sites referred to the press release and the related github project. This rather underwhelming public attention is not the result of a misguided project decision at Microsoft, but the exact opposite.

About our Blog

This blog is a place for us to reflect on data science, AI, and machine learning. Hence, it covers a broad array of topics: technical considerations, our view on certain industries, interviews with researchers, thought leaders, and industry experts, as well as light-weight visualisation.

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idalab seminar #8: Data Science meets art: Predicting bestselling books

Is there such a thing as “Bestseller DNA”? And how could it be revealed to authors, publishers or other interested parties? On March 2nd 2018, you have the chance to find out. In the context of the next idalab seminar, we will host a talk by Dr. Ralf Winkler, Founder and Managing Director of QualiFiction GmbH. QualiFiction is a young Startup based in Hamburg and Berlin, dedicated to Literature and Data Science. Their mission is to understand and extract the core characteristics that form a literary fiction text in order to predict the next bestseller that millions of readers will love.

Data Trails No. 9 – Snapshots from the history of data visualisation

Picture this: you need to plot data describing two large geographic entities, spanning the enormous period of 1,700 years, and you have no interactive tools at hand. No software, no templates, no filter, no button, no zoom, no switch. How in the world are you going to create a compelling visualisation for this data set, one that enables both overview and insight into the details?

idalab seminar #7: Next generation product search at Zalando using deep learning

On January 26th 2018, idalab will host a talk by Duncan Blythe, who is a Research Scientist at Zalando SE. He will give a talk on: Next generation product search in e-commerce using deep learning.

Legal Tech: Wie wird die Digitalisierung des Rechts vonstattengehen? Noch haben wir die Wahl!

Nach der Kommunikationsbranche, der Wirtschaft und der Industrie hat die Digitalisierung mittlerweile unverkennbar auch das Recht erreicht. Dass diese Entwicklung nicht mehr aufzuhalten ist, bestreitet eigentlich keiner. Unklar ist, was genau passieren wird und wie lange es dauern könnte bis was auch immer, in welcher Form auch immer, eintritt.

Data Trails No. 8 – Snapshots from the history of data visualisation

Oh, the Mississippi. The „Father of Waters“ is a heroic beauty with an eventful history, famous for its tendency to meander. At times, it poses a major threat to the people living along its shore. The list of Mississippi River floods is long and rather scary. It also happens to be a major commercial waterway, and these two aspects are at the heart of why the US Army Corps of Engineers has long been in charge for works in and along the river: in order to shield residents from floods, and to procure unobstructed navigation.

Data Trails No. 7 – Snapshots from the history of data visualisation

Timelines seem like such a „natural idea“ these days that we don’t even notice their ubiquity anymore: Facebook timeline, news feeds, graphic interfaces for back-up versions – how did anyone manage their life before there were things like this? Timelines are a universal concept to structure an overwhelming wealth of material, and the idea of time moving along a straight line is deeply engrained in our brains nowadays. However, this has not always been the case.

What would you recommend?

Personal recommendations are probably the strongest referral. If your friends tell you to checkout a restaurant they recently discovered, you are highly likely to follow their advice (assuming a general level of trust between you and your friends). For e-commerce companies and online platforms, recommendations are of critical importance. No wonder that plenty of research has been attributed to the development of the “perfect” recommendation engine.

idalab seminar #6: Jeremiah Lewis and Edouard Malet from N26

On December 1st 2017, idalab will host a talk by Jeremiah Lewis and Edouard Malet from N26: ‘Lean’ Training Data: An Incremental Approach to Supervised Machine Learning.

Data Trails No. 6 – Snapshots from the history of data visualisation

Do you know that thing when you draft a project and anticipate it will come out nicely, and once you actually start looking into it things get really complicated? This is what happened to me with this severe beauty of a tree diagram here. I stumbled upon it in the Beinecke digital collections and was immediately thrilled about this hidden gem from back in 1608. Then I never came around to really studying it — until just now.