From the course: Building Recommender Systems with Machine Learning and AI

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Intro to convolutional neural networks (CNNs)

Intro to convolutional neural networks (CNNs) - Python Tutorial

From the course: Building Recommender Systems with Machine Learning and AI

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Intro to convolutional neural networks (CNNs)

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of just using a simple multi-layer perceptron to solve a wide variety of problems. But you can kick things up a notch. You can arrange more complicated neural networks together and do more complicated problems with them. Let's start by talking about convolutional neural networks, or CNNs for short. Usually, you hear about CNNs Technically, we call this feature-location invariant. That means that if you're looking for some pattern or some feature in your data, but you don't know where exactly it might be in your data, a CNN can scan your data and find those patterns for you wherever they might be. For example, in this picture here, that stop sign could be anywhere in the image, and CNN is able to find that stop sign no matter where it might be. Now it's not just limited to image analysis. It can also be used for any sort of problem where you don't know where the features you have might be located within your data. Machine translation or natural language processing tests come to mind…

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