What are some current trends in deep learning research that build upon the foundations of perceptrons? What is the relationship between perceptrons and Boolean logic?
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what is perceptron Informational
- How does the bias term shift the decision boundary? Illustrate the decision boundary of a perceptron with a simple example in 2D.
- How can a multi-layer perceptron be used for multi-class classification? What are different output layer activation functions for multi-class classification (e.g., softmax)?
- What are adaptive learning rate methods (e.g., AdaGrad, RMSprop, Adam)? How do adaptive learning rate methods improve upon standard gradient descent?
- What is few-shot learning?
- How can bias in training data affect the performance and fairness of a perceptron? What are techniques for mitigating bias in machine learning models?
- How does the learning rate affect the step size in weight updates?
- What is the bias-variance trade-off in machine learning models?
- How can we develop more biologically plausible learning rules for artificial neural networks?
- How can perceptrons be used in natural language processing (NLP)? How can perceptrons be used in computer vision tasks?
- What is bagging, and how can it improve the robustness of a perceptron model? What are random forests, and how are they related to decision trees and perceptrons?
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