4 Data Science grads in Berlin have been involved with O’Reilly Media in the German translations of 3 key books. We’re super proud! Read on for more info on the books 👇.
Generatives Deep Learning
(Marcus Fraaß, Konstantin Mack, our first Data Science graduates! Cohort: One-Hot Chilli Peppers)
GANs are currently the avant-garde of deep learning systems. They generate artificial images, texts and sounds. The complexity of the subject makes them a very demanding subject to understand, because deep learning in itself is already complex. The book covers a wide of examples from all domain, all of which are “safe to try at home”. So the reader gets an introduction to the concepts of this fascinating class of models.
Datenvisualisierung Grundlagen und Praxis
(Bilgehan Gür, cohort: Linear Lavender)
This book covers one of the most fundamental data topics: making plots. On a few hundred pages, all types of data and plots are discussed with examples. The author annotates the plots as “good”, “ugly”, “bad” and “wrong”. In my opinion, a genius move was to include not a single line of code. Claus Wilke knows very well that the libraries for plotting come and go rapidly, and IT books generally go out of date quickly. Not this one. I believe that Bilgehans translation is a timeless piece that should be useful for generations of Data Analytics and Data Scientists.
Deep Learning für die Biowissenschaften
(Helena Schock, cohort: Tensor Thyme)
The book covers a broad mix of examples from different subdomains of life science such as molecular structures, microscopy images and genetic data. The book is structured to create a basic understanding of the machine learning concepts and serves as an introduction to ML. The book uses several Python libraries to make the data handling and training of machine learning models approachable.