Cursuri de pregatire Advanced Deep Learning

ID de curs

dladv

Durata

28 ore (usually 4 days including breaks)

Cerințe

Good understanding of Machine Learning. At least theoretical knowledge of Deep Learning.

Sinoptic

Învățarea în mașină este o ramură a inteligenței artificiale în care computerele au capacitatea de a învăța fără a fi programate în mod explicit. Învățarea profundă este un subdomeniul de învățare a mașinilor care utilizează metode bazate pe reprezentări și structuri de date de învățare, cum ar fi rețele neuronale.

Machine Translated

Schița de curs

  • Machine Learning Limitations
  • Machine Learning, Non-linear mappings
  • Neural Networks
  • Non-Linear Optimization, Stochastic/MiniBatch Gradient Decent
  • Back Propagation
  • Deep Sparse Coding
  • Sparse Autoencoders (SAE)
  • Convolutional Neural Networks (CNNs)
  • Successes: Descriptor Matching
  • Stereo-based Obstacle
  • Avoidance for Robotics
  • Pooling and invariance
  • Visualization/Deconvolutional Networks
  • Recurrent Neural Networks (RNNs) and their optimizaiton
  • Applications to NLP
  • RNNs continued,
  • Hessian-Free Optimization
  • Language analysis: word/sentence vectors, parsing, sentiment analysis, etc.
  • Probabilistic Graphical Models
  • Hopfield Nets, Boltzmann machines
  • Deep Belief Nets, Stacked RBMs
  • Applications to NLP, Pose and Activity Recognition in Videos
  • Recent Advances
  • Large-Scale Learning
  • Neural Turing Machines

 

Mărturii

★★★★★
★★★★★

Categorii inrudite

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