What is loss function? Types of loss functions Activation functions CNN architectures Perceptron Multi layer perceptron Gradient descent Optimezers Python

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Accepted Answer

Loss function measures the difference between predicted and actual values. Various types of loss functions are used in machine learning.

Loss function is used to optimize the model by minimizing the error between predicted and actual values
Types of loss functions include mean squared error, cross-entropy loss, hinge loss, etc.
Activation functions are used to introduce non-linearity in the model, popular ones include sigmoid, ReLU, tanh, etc.
CNN architectures are used for image recognition tasks, popular ones include VGG, ResNet, Inception, etc.
Perceptron is a single layer neural network used for binary classification tasks
Multi layer perceptron is a neural network with multiple hidden layers used for complex tasks
Gradient descent is an optimization algorithm used to minimize the loss function
Optimizers are used to update the model parameters during training, popular ones include Adam, SGD, RMSprop, etc.
Python is a popular programming language used for machine learning tasks

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What is loss function? Types of loss functions Activation functions CNN architectures Perceptron Multi layer perceptron Gradient descent Optimezers Python