How do you evaluate the performance of a trained perceptron?
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what is perceptron Informational
- When is cross-entropy loss preferred over MSE? How does the choice of loss function affect the training process?
- What are epochs in the context of training a perceptron or MLP? What is batch size in training?
- What are common hyperparameters to tune (e.g., number of hidden layers, number of neurons, learning rate, regularization strength)?
- How can adversarial attacks fool a trained perceptron?
- What is the difference between the decision boundary and the activation in Adaline? What is the concept of margin in classification?
- What is self-supervised learning? How can we develop more energy-efficient neural network architectures?
- What are the characteristics of a good activation function?
- What are some common kernel functions used with perceptron-like models?
- How can we ensure data privacy and security in the context of training and deploying perceptron models? What are the potential societal transformations that could result from continued advancements in artificial intelligence driven by perceptron-like models?
- How can perceptrons be used in robotics and control systems? How can perceptrons be used in healthcare applications?
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