stream:// data science

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,

Computer Vision Basics in Microsoft Excel (using just formulas) - amzn/computer-vision-basics-in-microsoft-excel

We’re on a journey to solve and democratize artificial intelligence through natural language.

Machine learning is one of the hottest topics in computer science today. And not without a reason: it has helped us do things that couldn’t be done before like image classification, image generation and natural language processing. But all of it boils down to a really simple concept: you give the computer data and the computer then finds patterns in that data. This is called “learning” or “training”, depending on your point of view. These learnt patterns can be extrapolated to make predictions. How? That’s what we are looking at today.