From the course: Deep Learning: Image Recognition

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Developing image recognition systems

Developing image recognition systems - Python Tutorial

From the course: Deep Learning: Image Recognition

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Developing image recognition systems

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- Now let's go ahead and talk about the most important aspect, which is the image-recognition systems. Well, in this session, we will delve deeper into building a robust image recognition system using a convolutional neural network. We'll continue from our previous discussions and introduce a more systematic CNN model to tackle the CIFAR-10 dataset. Let's dive right in and list the components of our system. Number one, we load and pre-process data. Number two, we visualize sample images. Number three, we define the CNN model. Number four, we compile and train the model. Number five, save the model. Number six, visualize training and validation accuracy. And number seven, finally, we evaluate the model. Let's go ahead and talk about the system in a little bit more detail. First, as always, we start by loading and pre-processing our CIFAR-10 dataset. This involves normalizing the pixel values and converting class labels into one-hot encoded vectors. Next, we visualize the sample images.…

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