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Διαφάνειες

  1. Deep Learning
  2. Διαλέξεις
  3. Διαφάνειες
Completion requirements
    • 05. Optimization 05. Optimization
      • Optimization for Machine Learning - UCLx DeepMind DL2020.pdf Optimization for Machine Learning - UCLx DeepMind DL2020.pdf
      • Optimization_lecture.pdf Optimization_lecture.pdf
    • 06. CNN 06. CNN
      • 06.1. CNN lecture.pptx 06.1. CNN lecture.pptx
      • 06.2. Vision Beyond Classification.pdf 06.2. Vision Beyond Classification.pdf
    • 08. RNN 08. RNN
      • L8 -  DeepMind.pdf L8 - DeepMind.pdf
      • rnn lecture.pdf rnn lecture.pdf
    • 10. Autoencoders  Representation Learning 10. Autoencoders Representation Learning
      • Autoencoders - Representation Learning.pdf Autoencoders - Representation Learning.pdf
      • Autoencoders.ipynb Autoencoders.ipynb
    • 11. Generative Adversarial Networks 11. Generative Adversarial Networks
      • GAN_MNIST.ipynb GAN_MNIST.ipynb
      • Generative Adversarial Networks.pdf Generative Adversarial Networks.pdf
    • 01. CNN_resnet_DL intro.pdf 01. CNN_resnet_DL intro.pdf
    • 02. Linear Algebra DL.pdf 02. Linear Algebra DL.pdf
    • 03. DFFN.pdf 03. DFFN.pdf
    • 04. Regularization.pdf 04. Regularization.pdf
    • 07. ARIS.pdf 07. ARIS.pdf
    • 09. Transformers_Transfer Learning.pdf 09. Transformers_Transfer Learning.pdf
    • 12. GraphML-GNNs.pdf 12. GraphML-GNNs.pdf
    • 13. Deep Reinforcement Learning.pdf 13. Deep Reinforcement Learning.pdf
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