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#machine learning

Most clicked news

Top 10 Java stories of May: TIOBE Index, Spring Boot 2.3, Java 16 plans & more

Every month, we take a look back at our top ten most clicked topics. Last month was packed full of exciting news such as more info on Java 16 with its upcoming migration to Git and GitHub. Other top news include interviews on the programming language Julia, the visualization platform Grafana and the Node alternative Deno. In May, we also learned how to analyze big data using Java and saw C pass Java in the monthly TIOBE Index.

Interview with Jens Dahl Møllerhøj

Nordic language BERT models: “Languages with fewer speakers are underrepresented on the internet”

BERT models in Danish, Swedish and Norwegian have been released by the Danish company BotXO. We spoke to Jens Dahl Møllerhøj, Lead Data Scientist at BotXO, to find out more. See how these open source models differ from Google’s multilanguage BERT model, what can make creating NLP models for Nordic languages difficult, and where these models can be used.

Flatten the curve with AI

Could AI solve the COVID-19 crisis?

Artificial intelligence could help us fight the coronavirus crisis. AI can, for example, already identify pneumonia on a CT scan in seconds with a high degree of accuracy. See what other things it can do to help flatten the curve.

Interview with the creators of Julia

“Julia is comparable to Python for simple machine learning tasks and better for complex ones”

The initial release of the Julia programming language was eight years ago, in 2012. We spoke to the four creators of the language, Dr. Viral B. Shah, Dr. Jeff Bezanson, Stefan Karpinski and Prof. Alan Edelman, to find out whether Julia has been able to live up to their high expectations. They also went into detail about the various use cases Julia is applied to today, how the language compares to Python, and where it is headed in the future.

Deep learning with Python and C++

PyTorch 1.5 arrives with stable C++ frontend API

The second PyTorch release of the year has landed. PyTorch 1.5 brings some of the deep learning library’s previously experimental features into stable mode, including the C++ frontend API. Let’s take a closer look and see what that means—and what else has been updated in this release.