Convolutional Neural Networks in 60 Seconds!

"Have you ever wondered how facial recognition or self-driving cars work? It's because of CNNs — Convolutional Neural Networks."
CNNs are designed to recognize patterns in images. They start by using filters to scan small sections of an image, detecting simple features like edges and textures. These features are passed through multiple layers, with each layer learning more complex patterns such as shapes. `
Pooling layers help reduce the size of the data while keeping the most important details. Eventually, fully connected layers take all the learned features and make a final prediction — like recognizing a face or identifying a stop sign.
If the prediction is wrong, the CNN adjusts its filters using a process called backpropagation. Over time, it learns and improves — just like we do. Hit that like and subscribe button if you learned something new.

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