Autoencoders - EXPLAINED

Data around us, like images and documents, are very high dimensional. Autoencoders can learn a simpler representation of it. This representation can be used in many ways:
- fast data transfers across a network
- Self driving cars (Semantic Segmentation)
- Neural Inpainting: Completing sections of an image, or removing watermarks
- Latent Semantic Hashing: Clustering similar documents together.
And the list of applications goes on.

Clearly, Autoencoders can be useful. In this video, we are going to understand it's types and functions.

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REFERENCES

CLIPS

#machinelearning #deeplearning #neuralnetwork #ai #datascience

[atifadib]

This is the most underrated channel on youtube.

[ispeakforthebeans]

Why does this guy not have a million subscribers

[hamzanaeem]

You have great understanding in this particular domain but the way you get million of subscribers is that you should explain in deep that why there is only 1 bottle neck, why not 2 . How encoder compresses what is the working behind it, each and everything and explain it on student level so that it may understands very easily . But I appreciate your stuff . Keep it up Man !

[mohammedfareedh]

Man your voice is so clean and pleasant

[neuodev]

This is awesome explanation 🙌.
About to consider please don't show the subscribe button in the every 2 min it is very confusing. every thing except this look good 👍 . thnks

[seyha]

What a great work! Thanks for videos. btw, can you make any videos about Conv-decon network? how it's different with Auto-encoders?

[landoftheunknown]

n_h in 6:43 is number of hidden layers pr number of neurons in hidden layer. Also, are we considering only 1 hidden layer?
A very nice explanation though! I am preparing for an interview and this is like a gold treasure for me!

[amortalbeing]

6:42 why did you say, we are considering a sigmoid activation ? what would be different if I used another activation function such as RELU?

Would the kl term change?Do we apply this on all layers or only the last layer of the encoder ?

[cesarfaustoperez]

Autoencoders and encoder-decoder are equal?

[nagendran]

Can you make a video for the beginners, this stuff with formulas and equation gets too complicated.

[est]

9:37 can't a CNN do the same job? What's the difference between using CNN and autoencoders with convolutional layers? Or are they actually the same thing? I'm new to both types of networks, so would appreciate any elaboration. Thanks.

[spyzvarun]

Why do we need the encoder and decoder to be a shallow network?

[harshraj]

01:22 .. data around us like images and donkeynets