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sure, i'd be happy to provide a basic tutorial on implementing a convolutional neural network (cnn) for image classification in python using a popular deep learning library, tensorflow, along with its high-level api, keras.
python and libraries: make sure you have python installed on your system. install the necessary libraries using:
dataset: for this tutorial, we will use the cifar-10 dataset, which consists of 60,000 32x32 color images in 10 different classes. you can load this dataset directly from tensorflow.
let's start with a simple cnn architecture for image classification:
loading and preprocessing data:
defining the cnn model:
compiling the model:
training the model:
evaluating the model:
plotting training history:
this is a basic example to get you started with image classification using a cnn in python. feel free to experiment with different architectures, hyperparameters, and datasets for more advanced applications.
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