MIT 6.S191 (2023): Convolutional Neural Networks

This presentation is really well put together.

Alexander Amini has splendid presentation skills

Hi, After CNN performed, and pixels are flatten then can we add VAE with GAN to create the same probability distribution of input flattened array and as well some alternative derivativea Or distribution, like cycle gan, road to map.

Am I connecting it correct or again watch the videos,

Thank you for the videos

Where do I find the labs for the practice?

Great Lecture. Thank you very much!

Super 👍

love from india as I'm not able to study at MIT but this series helps me a lot and I hope lots of people but if you can add the labs lecture that how we can build this practically so it would be a great honor

Thank you :)

Thanks sir for this wonderful explanation.

Are NNs not always fully connected? I just assumed they were from the math, unless a given weight is zero.

This entire series on Deep Learning is a great pleasure to listen to and brainstorm about.

There are limitless possibilities for AI applications, and I'm highly inspired for some of them.

Wow, it's ridiculous, the more it goes, the better - I love every single minute of this course - A huge thank you!

Where can I find the Tensor Flow labs to practice?

hello, I'm giving a course at my university on Brazil about Machine Learning, and i would like to ask to use some of your slides and translate your material for the next leasson which is about CNN

I am in awe. You have delivered these concepts so beautifully that I didn't need to look up into other resources. I have recently made a switch to this field and you happened to be my biggest motivator to pursue it further. Thank you.

I get so excited about the use cases and various possibilities of using CNNs. Excellent presentation. A master class in simplifying a complex subject.

Thank you to the author. Does anybody get from this video how all this works with shift/rotation/scale of the image?

Thank you very much for sharing!

excellent.

Now i have learned the whole CNN working. Great explanation

The best tutorial of CNN on earth.

Thank you Dr

Can we get access to software labs with some hands on learning? I know codes are available but something else where we can learn from scratch.

Here's what I love about your lectures: You give the intuition and logic behind the architectures and this helps a lot as opposed to the stone tablet thrown down from the heavens approach. Not only is this important for learning but it also stimulates intuition for the next set of innovations!

I was very impressed when I heard that the transformer model was created by a Vietnamese person

I'm self-studying deep learning without going through any school so I need sharers like you . thank you very much!

Thank you for uploading this video ❤

Don't use dark theme for code: many chars are badly visible.

Hello Alexander,

Please make a dedicated video on "Reinforcement Learning with Human Feedback"

Convolution is a dot product, weighted sums are dot products. Max pooling is a switching decision, ReLU is (if you get your head straight) a literal switch with x>0 as the switching decision. Then all a neural network is is a collection of weighted sums / dot products that are connected and disconnected to and from each other by switches according to a switching decision predicate for each switch. You should see you are free to connect in cheap fast weighted sum algorithms like the FFT or WHT, make ReLU a 2 pole switch and many other things. There is a Walsh Hadamard transform booklet via archive.

Great Lecture, but last week Ava said this year's CV lecture will be about Vision Image Transformer!

the videos, slides and explanation keep getting better.

Wow !! Really awesome lecture Alex sir . Nice explanation with perfect slides

It's unbelievable that you're doing this for free. Thanks a lot Sir. Your explanation is very clear and in an easy manner. Thanks again Sir.

All man yone
2 videos blady chicken hahah

We are so lucky to be alive at a time when we can attend these types of lectures for free <3

Awesome!

Such a brilliant session! I am totally in the awe of this course, and loved the way Dr. Alex dissects the concepts in simplified way!

I wonder if the 2 AIs can argue each other. haha and there could be a problem if you have 100 AI. 😂

alex, i wanna ask you last lecture was sequencing in the website there's code lab related to that lecture can i walk through or you gonna assigning

the raw data comes from the universe where we live.

the spark is what the drive is, but the drive changes according to the input. but it is exhaustible, it is the human body that dies. that's your second problem hahaha
And now tell me if the program that runs in a person is created by genes or by that spark. I would describe it as a synopsis.

you try to figure out how to program the human mind, but you can't until you are able to create that spark of consciousness, that divine particle that makes a brain a brain.

The Convolutional Neural Network, one of my Passion and with MIT is an ART

if I were to describe to you how I perceive the world, you would turn the brown thing into a textile.