How would you implement a convolutional neural network (CNN) in MATLAB to classify images?

To implement a convolutional neural network (CNN) in MATLAB for image classification, you can follow these steps:

1. **Set Up Your Data**: Prepare your image dataset by splitting it into training and testing sets.

2. **Create the CNN Model**: Define the architecture of the CNN using layers such as convolutional, pooling, and fully connected layers.

3. **Compile and Train the Model**: Use the `trainNetwork` function to compile and train the CNN model with the training data.

4. **Evaluate the Model**: Evaluate the performance of the trained model using the testing data to assess its accuracy and effectiveness in classifying images.

5. **Optimize and Fine-Tune**: Consider optimizing the CNN model by adjusting hyperparameters, adding regularization techniques, or fine-tuning the network to improve its performance.

By following these steps, you can effectively implement a convolutional neural network in MATLAB for image classification. Remember to regularly optimize and fine-tune your model for better results.

**Focus keyword**: convolutional neural network (CNN) in MATLAB