Applied Analytics professor Siddhartha Dalal discusses the impacts of applied technologies on real-life risk management.

Explore the distinctions between the related but distinct technologies of deep learning and generative AI, along with their techniques, applications, strengths, and challenges. Written by eWEEK ...

Today Nvidia announced cuDNN, new software designed to help developers harness the power of GPU acceleration for deep learning applications in areas such as image classification, video analytics, ...

Microsoft shipped ML.NET 3.0, enhancing deep learning and data processing scenarios in the company's machine language framework that lets devs create AI-infused apps completely within the .NET ...

The study found that deep learning models, especially CNNs, were the most frequently implemented technique (61.2%), followed ...

In the podcast, Rosaria Silipo talks about the emerging trends in deep learning, with focus on low code visual programming. BT. ... no-code techniques for using deep learning in your applications.

A key advantage of deep learning-based algorithms over legacy computer vision algorithms is that deep learning system can be continuously trained and improved with better and more datasets. Many ...

Deep learning is a set of techniques for learning in neural networks that involves a large number of “hidden” layers to identify features. Hidden layers come between the input and output layers.

Deep learning is particularly effective in recognizing unstructured data, including sounds, images, clips and documents. Deep learning is utilized mainly in applications supporting big data sets ...