Teaching yourself deep learning is a long and arduous process. You need a strong background in linear algebra and calculus, good Python programming skills, and a solid grasp of data science, machine ...

Not every regression or classification problem needs to be solved with deep learning. For that matter, not every regression or classification problem needs to be solved with machine learning. After ...

Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment The importance of machine learning and deep learning is no longer in ...

In this video from the 2019 OpenFabrics Workshop in Austin, Xiaoyi Lu from Ohio State University presents: Accelerating TensorFlow with RDMA for High-Performance Deep Learning. Google’s TensorFlow is ...

TensorFlow, the open-source platform for machine learning, has just received its final release for version 2.0. According to the company's official Medium blog, the update brings a set of new features ...

Google last week open sourced TensorFlow, a new machine learning library used in deep learning projects. Even though the Web giant has just started using the software in its products, it apparently ...

Despite some of the inherent complexities of using FPGAs for implementing deep neural networks, there is a strong efficiency case for using reprogrammable devices for both training and inference.

Researchers at Google and Intel recently collaborated to extract the maximum performance from Intel® Xeon and Intel® Xeon Phi processors running TensorFlow*, a leading deep learning and machine ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More At Google’s inaugural TensorFlow Dev Summit in Mountain View, California, ...