Deep Learning: A Crash Course (2018) | SIGGRAPH Courses

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Publicado 2018-08-12
Deep learning is a revolutionary technique for discovering patterns from data. We'll see how this technology works and what it offers us for computer graphics. Attendees learn how to use these tools to power their own creative and practical investigations and applications.

Originally presented at SIGGRAPH 2018.

PRESENTER
Andrew Glassner, The Imaginary Institute


LEARN MORE
ACM DIGITAL LIBRARY: dl.acm.org/doi/10.1145/3305366.3328026
ACM SIGGRAPH: www.siggraph.org/

Todos los comentarios (21)
  • @plague0
    i fall asleep with youtube on and now im waking up to this lmao
  • In 2024, Don't set new year financial goals without consulting a financial adviser. Their expertise ensures a solid plan for success. Building wealth involves developing good habits like regularly putting money away in intervals for solid investments.
  • @louis9116
    If I had to choose only 1 video to watch on Deep Learning on YouTube I would, without a doubt, pick this video. Superb teaching style.
  • @MarcusFred-wn3iv
    Been watching, listening, and paying attention to all of predictions and forecasts since early Covid. He hasn't disappointed yet 👌
  • @leixun
    My takeaways: 1. Artificial Intelligence (AI) vs Machine Learning (ML) vs Deep Learning (DL) 4:36 2. What is intelligence 6:27 3. Deep learning applications 7:05 4. Unsupervised learning, reinforcement learning and supervised learning 11:04 5. Training and test, with examples 16:28 6. Classification, k-mean classifier 31:05 7. Neurons 35:35 8. Fully-connected layers 40:45 9. Activation functions, softmax 46:16 10. Loss, cost 52:12 11. Gradient descent 55:45 12. Backpropagation 1:03:30 13. Learning with gradient descent, learning rate, convergence 1:07:46 14. Data 1:19:36 15. Dimensionality reduction, Principal Components Analysis (PCA) 1:21:22 16. Evaluating accuracy: across-validation 1:27:30 17. Overfitting and underfitting, regularization (e.g. dropout) 1:48:10 18. Convolution, with examples 2:01:55 19. Autoencoder, latent variables, variational autoencoder, denoising 2:33:00 20. Reinforcement learning, Q learning 2:46:38 21. Recurrent Neural Networks 2:54:25 22. Generative adversarial networks (GANs), deep dream, style transfer 2:58:22 23. Ethics 3:20:46
  • @utkumertt
    I opened the video by mistake and now I can not leave. Good presentation!
  • @marvin8656
    i watched food Theory and sleept away now im 3hours inside deep learning
  • @anotherplatypus
    Felt like a 3.5 hour Ted Talk... that guy is such a rare, damned good, CS teacher... wow.
  • @Kassem_Bagher
    There is always an answer to every question that pops into my head! Can't thank you enough 👏🏼
  • Wow. Amazing. Thank you - great lecture. I never suspected that a 3+ hr. lecture could be so interesting!
  • @Mac_Daffy
    single best thing I‘ve seen on the internet today (after watching 3 hours there wasn‘t much time left to browse the others).
  • @thenoideaman
    Quality stuff, great content and way of presenting it, one of the best tech lectures I've seen on youtube.
  • @belkassem06
    Woooww He just compiled my entire semester classes un one course of 3 hours, amazing. Great and Thanks for that.
  • The concepts are so clearly explained i like that. It was really nice to watch Great content, awesome explanations, great job. the best explanation of deep learning I've seen
  • Thank you Andrew & SIGGRAPH for sharing this excellent introductory lecture on deep learning!
  • Definitely one of the best lectures on Deep Learning. Andrew's teaching style and delivery makes this otherwise hard subject so easy to understand. The concepts are so clearly explained that even the first time audience can grasp the bulk of it if not all. It was really exhilarating to watch and listen to this whole lecture and dispel any misconceptions about certain techniques that may have been misconstrued or unintentionally taught wrong by others. I definitely learned a lot from it. Thank you sir for making this video available to all and to learn from.
  • @demonhunter4709
    SIGGRAPH please don't delete these videos Bcuz i had seen that there are no videos of last year Please don't delete it as Its valueable to new peoples, this lectures motivates us to study more about COMPUTER GRAPHICS I'm sure that we new peoples will give SIGGRAPH more researchers in few years Please support cummunity by giving them valueable lectures 😇😇😇
  • @clearwavepro100
    Thank you Andrew Glassner for sharing this information, translating it, preparing it and metaphorizing it. Thank you for speaking up about ethics as well.
  • I've been working with this in the background. When they took break... I got such a (pleasant) surprise when he called "1 minute", I'd forgotten this lecture was still happening.