Autoencoders Made Easy! (with Convolutional Autoencoder)

What is an autoencoder? How do they work? How to build your own convolutional autoencoder?
#autoencoders #machinelearning #python

Chapters
0:00 Introduction
3:10 Mathematical Concept
7:00 Vanilla Autoencoder
15:08 Convolutional Autoencoder

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[ThefamousMrcroissant]

This is an unusually well structured video. Not only do you go over the "what and why?", but you also provide a demonstration, visualisation and notebook file in case you wish to look it up yourself. Excellent work.

[sabazainab]

Great content. Watched your video just for the sake of Convolutional Autoencoders but you didn't define it clearly and not made any video further on it. Btw you teach amazingly in a very easy way. Love from Pk

[zakiamahmoudi]

thank you for this 'rich' and amazing video.

[pranavgupta]

Hi, you mentioned Autoencoders as Jack of Trades, could you give an example of feature selection or dimensionality reduction algorithm which outshines Autoencoders?
Thank you

[theankitkurmi]

we can surely upscale the generated cat images using super resolution techniques. great video <3 :-)

[kaveeshasenanayake]

Very well explained. Thank you so much.

[boira_dani]

Great video and explanation, thank you! :)

[gopikasnair]

please do a video on calculating mse and anomaliy detetction

[new_beginning]

you said It is self-supervised learning, but can i used Annotated data with this CNN autoencoder?
I have to do sematic segmentation, and the output is also an image.
input are image and few sensor data. and i have annotated the features in the image.
What model do you think i should use.?

[ellisiverdavid]

I’m just wondering—after we obtained the most important features from the bottleneck of our trained neural network, is it possible to implement the denoising capability of the autoencoder to a live feed video that is somewhat highly correlated to the training images? For instance, CCTVs?

Will this be better, or even recommended, instead of using traditional denoising filters of OpenCV for real-time videos?

I’d love to learn more from your expertise and advices as I explore this topic further.

Anyway, thank you so much for the insightful explanation and demo by the way! This is undoubtedly one of the most in-depth and easy-to-digest explanations out there. I do like your high energy and enthusiasm, and also the fresh and flexible implementation using the cat dataset instead of the usual MNIST dataset. Great work! 💯

Subscribed :)

[mehdiorouji]

Thanks for the tutorial! You mentioned conv2Dtranspose is the same as conv2D if the padding is the same. If so why you are you using conv2Dtranspose? And why the last layer of CAE is Conv2D and not Conv2Dtranspose?

[yashmore]

Hii this is great! Can you also explain variational autoencoders!!?

[shriyanarayan]

Sir is there anyway to implement this to moving objects like movement is 360

[pranavkushare]

Could you please tell me which are better models than autoencoders for the same task ?

[moumitamoitra]

suppose i have 200 training image then can I use autoencoder?

[zebcode]

It would have been much better if you'd built the network as you went instead of just showing to finished article. Seeing mistakes is often more valuable.

[belhafsiabdeldjalil]

I want to adapt your code on my 79by79 images

[hejarshahabi]

For a sec I thought an IS member is on youtube, for god sake take off that hair. anyway, thanks for the video it is helpful.

[redfruitz]

omg balance your sound volume! that thing is exploding my hear drums more than Piper Perry on couch with 5 blacks.