Each algorithm is built for a different type of problem, and they all engage in subtly different kinds of machine learning. Here, we'll discuss four major subtypes of software neural networks: ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision ...

As the name suggests, neural networks are inspired by the brain. A neural network is designed to mimic how our brains work to ...

Liquid Neural Networks could help us to achieve the next level of efficiency with AI/ML Many of us can agree that over the past few years AI/ML progress has been, well, rapid. Now, we’re given yet ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...