The Evolution of Neural Networks

Have you ever thought about how a simple math model can turn into a complicated visual processing engine? In this video, we explain the main differences between Convolutional Neural Networks (CNNs), Multi-Layer Neural Networks (MLPs), and Single-Layer Perceptrons.

We go into great detail about:
Single-Layer Networks: Their building blocks and how they don't work well with non-linear data.
Multi-Layer Networks: How "hidden layers" make it possible to solve hard problems.
CNNs: Why they are the best at recognizing images and making spatial hierarchies.

This comparison will help you figure out which architecture to use and when, whether you're a data science student or just curious about how AI "thinks."

Видео The Evolution of Neural Networks канала The Query Quest