Neural Networks – Lecture 5 – CS50's Introduction to Artificial Intelligence with Python 2020




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00:00:00 – Introduction
00:00:15 – Neural Networks
00:05:41 – Activation Functions
00:07:47 – Neural Network Structure
00:16:02 – Gradient Descent
00:30:00 – Multilayer Neural Networks
00:32:58 – Backpropagation
00:36:27 – Overfitting
00:38:52 – TensorFlow
00:53:01 – Computer Vision
00:58:09 – Image Convolution
01:08:18 – Convolutional Neural Networks
01:27:03 – Recurrent Neural Networks

This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.

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LICENSE

CC BY-NC-SA 4.0
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License
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David J. Malan
https://cs.harvard.edu/malan
malan@harvard.edu

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Comment List

  • CS50
    November 14, 2020

    Very helpful video. Great job!!

  • CS50
    November 14, 2020

    51:53 When I run the source code, Brian has this 823/823 for training samples and 549/549 for his test samples but mine is 26/26 and 18/18 respectively…(the accuracy for mine is still like 98% or something though) anyone knows why?

  • CS50
    November 14, 2020

    Learned much more than whole semister of my College.

  • CS50
    November 14, 2020

    I learned a lot — you are a great instructor indeed!

  • CS50
    November 14, 2020

    Is it recommended to take down notes?

  • CS50
    November 14, 2020

    Could it be that there is no explanation on how exaclty the filter kernerls are learned? Or am I just missing it? It' something that interests me quite a lot but i don't seem to find the explanation….
    Also great content!! Been a fan of Cs50' computer science introduction already and now this course is just ideal to gain some pratical knowledge related to ML! Awesome that educational information is provided for free in such a great and qualitative way! Thanks!

  • CS50
    November 14, 2020

    Nice content Brian!
    Do you know how Alpha Zero was written

  • CS50
    November 14, 2020

    Why Publishing videos so late.? Even videos were available on CDN in Feb. Seems like YouTube is no more a considerable platform for edx.

  • CS50
    November 14, 2020

    Please put the timestamps.

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