Underfitting in a Neural Network explained

In this video, we explain the concept of underfitting during the training process of an artificial neural network. We also discuss different approaches to reducing underfitting.

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[Mahdi-noori-ai]

i'm a deep learning programmer and after 6 years that this playlist has been published . its absolutely still insane 😍

[zahidullah]

believe me, I have gone through hundreds of DL videos but couldn't understand them. But you made DL so much easier. Each video in the playlist is becoming easier instead of getting complex.

[karelhof]

really great and underappreciated channel. Plan to see all of the rest of your videos as well, it's a great explanation on a very difficult topic

[tymothylim]

Thank you very much for this video! The animations really help me understand the various methods for tackling underfitting!

[qusayhamad]

thank you very much for this clear and helpful explanation.

[michaelmuller]

The point about dropout was helpful! Thanks!

[gourabsarker]

Thank You Very Much for this!!! ❤️❤️

Please, if you can, try to make a detailed video on Dropout !

Thank You again!Best of Luck!

[kyla]

{
"question": "When training a neural network, we can reduce underfitting by",
"choices": [
"decreasing dropout rate",
"making small changes to the learning rate",
"removing data from the training set",
"increasing dropout rate"
],
"answer": "decreasing dropout rate",
"creator": "Kyla",
"creationDate": "2021-04-17T02:41:56.637Z"
}

[guillaume]

Thanks for this video but concretely, what do mean :
- Increase the number of layers in the model?
- Increase the number of neurons in each layer?
- Changing what type of layer we are using where?
(Question from a newb who starts taking up learn about ML, sorry)

[fritz-c]

I spotted a slight typo in the article for this video

improve it’s accuracy
↓
improve its accuracy

[saluk]

{
"question": "The problem of underfitting in a neural network can be tackled in all of the following ways except:",
"choices": [
"Increasing the amount of data through data augmentation",
"Increasing the complexity of the neural network model",
"Increasing the number of features that are used in the data",
"Decreasing the rate of dropouts in layers that have them"
],
"answer": "Increasing the amount of data through data augmentation",
"creator": "saluk",
"creationDate": "2020-08-27T15:49:02.774Z"
}

[carlosmontesparra]

what is the point of dropout when you can set the number of nodes in each layer? At first the only difference I see is that dropout does not affect the validation test, why would we prefer dropout over resetting number of node?

[keliletilki]

{
"question": "Underfitting is simply an unsuccesfull training",
"choices": [
"True",
"False",
"Kinda",
"Not at All"
],
"answer": "True",
"creator": "Tilkikelile",
"creationDate": "2021-11-30T00:07:18.358Z"
}

[aravindvenkateswaran]

What is the point of the validation set if it doesn't validate on dropouts that we designed? Is it just a feature to debug the underfitting problem?

[roger_is_red]

So how can a company like tesla be sure that its neural net has enough capacity to learn level 5 self driving in other words are there ways to compute the learning capacity of a neural net?

[srikarvalluri]

Hi deeplizard,


What do you mean when you talk about reducing complexity? I know that your talking about decreasing the number of nodes in a layer, but how does that help overfit or underfit? In fact, an even more essential question, how does the number of nodes in a layer help or harm data?


Thanks for your videos btw.


Srikar

[-arabsoccer]

actually i did not get why the underfitting is happened ? can u explain it more
If i understand well, it will be happen if the model can figure out the trained data well, and can figure out the un trained data but with low level of expectation and this can be detected by the error function when we run out model

[thespam]

{
"question": "Which of the following is most indicative of underfitting?",
"choices": [
"A model is unable to classify data in the training set",
"A model is unable to classify data outside the training set",
"A model has input/output sizes that are too large",
"A model has input/output sizes that are too small"
],
"answer": "A model is unable to classify data in the training set",
"creator": "Chris",
"creationDate": "2019-12-11T05:02:20.900Z"
}

[Akshatgiri]

I love your videos alot and thanks alot for making them. But can you please *please* change the intro and outro sound ( noise ) in the new videos ( if you already have, please ignore this comment ). They are creepy af.