Covers: theory of Back Propagation
Estimated time needed to finish: 210 minutes
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Deep Learning Model Training And Optimization

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Total time needed: ~6 hours
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INTERMEDIATE
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Resources5/6
VIDEO 1. Loss Functions
  • What is the relevance of loss functions for deep learning?
17 minutes
VIDEO 2. Optimization using Gradient Descent - Part 1
  • How do neural networks learn?
26 minutes
VIDEO 3. Optimization using Gradient Descent - Part 2
  • How do you use gradient descent for parameter updating?
17 minutes
VIDEO 4. Chain Rule, Backpropagation & Autograd
  • How else can I train my neural nets?
21 minutes
REPO 5. Hands-on Optimization
  • How to implement optimization methods in PyTorch?
  • How can we update parameters with Gradient Descent?
  • How to implement gradient descent in Pytorch?
30 minutes
RECIPE 6. Understanding BackPropagation
4 hours

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