NLP Reading Group, Dhaka

Deep Learning

Tutorial 2 - Training Deep Neural Networks

Tahnik Ahmed

  1. Reviewing the Concepts of Neural Networks (Basic Architecture, Model Representation Mathematics)
  2. Forward Propagation Calculation
  3. Backward Propagation Algorithm (Mathematics & Visualizations)
  4. Training a deep neural network model with MNIST Fashion Dataset (Tensorflow) i) Hyperparameters ii) Hyperparameters Tuning Simulation (TF Playground & simulations)
  5. Brief of Autograd (PyTorch Implementation)
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