Indiafilings Interview Questions, Process, and Tips

Q1. What is the difference between sigmoid and softmax activation function?
Ans. 
Sigmoid is used for binary classification while softmax is used for multi-class classification.
• Sigmoid function outputs values between 0 and 1, suitable for binary classification tasks.

• Softmax function outputs a probability distribution over multiple classes, summing up to 1.

• Sigmoid is used in the output layer for binary classification, while softmax is used for multi-class classification.

• Softmax is the generalization
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Q2. What is an activation function ?
Ans. 
An activation function is a mathematical function that determines the output of a neural network.
• Activation functions introduce non-linearity to the neural network, allowing it to learn complex patterns in the data.

• Common activation functions include sigmoid, tanh, ReLU, and softmax.

• The choice of activation function can impact the performance and training speed of the neural network.
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