Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN Loss Function in PyTo

Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN Loss Function in PyTo

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Information Technology (IT), Architecture

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The video tutorial introduces the concept of activation functions in neural networks, focusing on the sigmoid function. It explains how to define and use loss functions, particularly binary cross entropy, to measure model performance. The tutorial encourages experimenting with different loss functions available in Pytorch. It concludes with a preview of the next topic, gradient descent, which is crucial for optimizing network parameters.

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OPEN ENDED QUESTION

3 mins • 1 pt

What new insight or understanding did you gain from this video?

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