Dropout Layer in Deep Learning | Dropouts in ANN | End to End Deep Learning
Channel: CampusX
Date: 2022-05-12

Dropout is an approach to regularization in neural networks which helps reduce interdependent learning amongst the neurons. Dropout is used as a regularization technique in order to reduce overfitting.

Digital Notes for Deep Learning: https://shorturl.at/NGtXg

Dropouts original paper - https://jmlr.org/papers/volume15/srivastava14a/srivastava14a.pdf

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✨ Hashtags✨
#DeepLearningExplained #DropoutLayers #NeuralNetworks101

⌚Time Stamps⌚

00:00 - Intro
01:25 - Problem of Overfitting
03:52 - Solutions for Overfitting
06:08 - Dropouts
13:14 - Why it works?
18:50 - Random Forest Analogy
23:45 - How prediction works?
27:10 - Outro