MIT 6.S191 (2023): Convolutional Neural Networks
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Published 2023-03-24
Convolutional Neural Networks for Computer Vision
Lecturer: Alexander Amini
2023 Edition
For all lectures, slides, and lab materials: introtodeeplearning.com/
Lecture Outline
0:00 - Introduction
2:37 - Amazing applications of vision
5:35 - What computers "see"
12:38- Learning visual features
17:51 - Feature extraction and convolution
22:23 - The convolution operation
27:30 - Convolution neural networks
34:29 - Non-linearity and pooling
40:07 - End-to-end code example
41:23 - Applications
43:18 - Object detection
51:36 - End-to-end self driving cars
54:08 - Summary
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All Comments (21)
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We are so lucky to be alive at a time when we can attend these types of lectures for free <3
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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.
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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!
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Thanks Alex Amini and MIT ) 🥰😊
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the videos, slides and explanation keep getting better.
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we are waiting Thanks Alex Amini
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Thanks Alex for sharing these lectures online. A quick comment about fully connected layer causing loss of spatial information @14:40. I don't think fully connected layers result in spatial information loss. All your network has to do is identify that certain indices in the flattened vector correspond to specific locations in the spatial map. We can lose some translation/spatial invariance but not necessary spatial information loss.
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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.
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I'm self-studying deep learning without going through any school so I need sharers like you . thank you very much!
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This presentation is really well put together.
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Thank you very much for sharing!
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Thank you for uploading this video ❤
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Great Lecture. Thank you very much!
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Hello Alex! It’s great to join your class here 👍
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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!
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we are waiting excitingly 😀
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The Convolutional Neural Network, one of my Passion and with MIT is an ART
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Wow !! Really awesome lecture Alex sir . Nice explanation with perfect slides
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Greatly thankful to your efforts for making this great lectures free and so easily accessible, thank you Alexander Amini
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I really appreciate you posting this material!! Thank you 🙏
