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Deep Learning Fundamentals - Full Stack Deep Learning

Deep Learning Fundamentals - Full Stack Deep Learning

The Full Stack via YouTube Direct link

- Intro

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- Intro

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Deep Learning Fundamentals - Full Stack Deep Learning

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  1. 1 - Intro
  2. 2 ​ - Neural Networks
  3. 3 ​ - Universality
  4. 4 ​ - Learning Problems
  5. 5 ​ - Empirical Risk Minimization / Loss Functions
  6. 6 ​ - Gradient Descent
  7. 7 ​ - Backpropagation / Automatic Differentiation
  8. 8 ​ - Architectural Considerations
  9. 9 ​ - CUDA / Cores of Compute

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