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Deep Learning

Сomputational resource

  1. Google Colab
  2. Google Cloud Platform

Neural Networks: Theory

  1. Introduction.
  2. Data-driven approaches.
  3. Simple linear classifier, Loss function.
  4. Backpropagation and NN.
  5. Multilayer NN, Activation, Loss.
  6. Normalization, Convolution.
  7. Recurrent Neural Networks.

Neural Networks: Applications

  1. Semantic segmentation, Keypoint detection, and Object detection.
  2. Text-to-Speech.
  3. Natural Language Processing - BERT and The History Behind It.
  4. Data management.
  5. NN Inference.

Neural Networks: Practice

  1. Task #1 - Simple data-driven approach and results.
  2. How to use training frameworks:
  1. Task #2 - Multilayer neural network and results.
  2. Symbol 'H' to sequence 'HELLO' with RNN: Download.