Reinforcement Learning and Deep RL Python Theory and Projects - DNN Why Activation Function Is Required Exercise Solutio

Reinforcement Learning and Deep RL Python Theory and Projects - DNN Why Activation Function Is Required Exercise Solutio

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Information Technology (IT), Architecture, Mathematics

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The video tutorial explores the concept of neural networks with linear activations and a single sigmoid-activated neuron in the last layer. It explains how such a structure collapses into a linear layer followed by a sigmoid, resembling logistic regression. The tutorial clarifies that logistic regression is not typically considered a neural network, despite its perceptron-like structure. It concludes that introducing non-linear activations in hidden layers transforms the model into a neural network.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What happens to the layers of a neural network if all hidden layers have linear activations?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

How is logistic regression related to neural networks?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the significance of having a nonlinearity in the last layer of a neural network?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

Why might logistic regression not be classified as a neural network?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What conditions must be met for a model to be considered a neural network?

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