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This article covers a thorough introduction to geometric deep learning, including interesting use-cases like graph segmentation, classification, and KGCNs.

Introduction In March 2020, ML.NET added support for training Image Classification models in Azure. Although the image classification scenario was released in late 2019, users were limited by the resources on their local compute environments. Training in Azure enables users to scale image classification scenarios by using GPU optimized Linux virtual machines.

Whether you're actively implementing deep learning now or just starting to learn about it, we would love to hear your feedback to shape upcoming support.

Data Science fwdays'19 conference: https://fwdays.com/en/event/data-science-fwdays-2019/review/natural-language-processing Moderator: Vitaliy Radchenko (Data...

Coca-Cola is a well-known soft drink manufacturing company which has been rapidly adopting artificial intelligence. This article explains how they do it.

Google launched the COVID-19 Public Datasets program, which will provide coronavirus data sets to researchers at no charge.

With more board configurations than there are atoms in the universe, the ancient Chinese game of Go has long been considered a grand challenge for artificial...

With the spread of COVID-19 becoming an evermore assertive force in our lives, the healthcare data science community has an opportunity to play an important role in the mitigation of this emerging pandemic.  History has shown response to such diseases can drastically alter the worst effects of such diseases.  Many cities have imposed social distancing …

One of the most exciting things in our work is offering new ways for you to incorporate your own ideas and vision into our tools. In this blog post, I would like to highlight a feature that is especially interesting in that regard and came in with our end-of-January release: Custom compilation steps,