Attention Mechanism - Introduction to Deep Learning

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  • Опубліковано 3 жов 2024
  • This video explains the basic structure of the neural network, Attention.
    It has recently been very popularly used in Deep Learning alongside Convolutional Neural Networks.
    Previous : Downsizing Neural Networks by Quantization
    • Downsizing Neural Netw...
    Basics of Designing Neural Network
    • Basics of Designing Ne...
    The Mechanism of Neural Network Training
    • The Mechanism of Neura...
    What are Recurrent Neural Networks?(RNN)
    • What are Recurrent Neu...
    Understanding LSTM without Mathematical Expressions (Long Short-Term Memory)
    • Understanding LSTM wit...
    Neural Network Console UA-cam Channel
    / neuralnetworkconsole
    Playlist : Introduction to Deep Learning
    • Introduction to Deep L...
    Neural Network Console
    dl.sony.com/
    Neural Network Libraries
    nnabla.org/
    Squeeze-and-Excitation Networks
    Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu
    arxiv.org/abs/...
    Attention Is All You Need
    Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin
    arxiv.org/abs/...
    BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
    Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova
    arxiv.org/abs/...
    *NOTE*
    This contents has been translated from Japanese into English.
    The original has been published on January 23, 2020.
    • Deep Learning入門:Attent...

КОМЕНТАРІ • 6

  • @paps0n
    @paps0n Рік тому +13

    what's wrong with this piano

  • @feras6471
    @feras6471 Рік тому +8

    The music is Awful

  • @HamedPoursiami
    @HamedPoursiami 7 місяців тому +2

    The background music is extremely annoying!

  • @SYEDHASEENA-c5q
    @SYEDHASEENA-c5q Рік тому

    How can I add 'Attention mechanism' to Vector Quantized Diffusion Model for Text-to-Image Synthesis?

  • @maryamsajid8400
    @maryamsajid8400 2 роки тому +2

    good explanation but too fast