MIT Introduction to Deep Learning - Foundations of Deep Learning - Lecture 1

MIT Introduction to Deep Learning - Foundations of Deep Learning - Lecture 1

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​ - Introduction

1 of 13

1 of 13

​ - Introduction

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MIT Introduction to Deep Learning - Foundations of Deep Learning - Lecture 1

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  1. 1 ​ - Introduction
  2. 2 ​ - Course information
  3. 3 ​ - Why deep learning?
  4. 4 ​ - The perceptron
  5. 5 ​ - Perceptron example
  6. 6 ​ - Applying neural networks
  7. 7 ​ - Loss functions
  8. 8 ​ - Training and gradient descent
  9. 9 ​ - Backpropagation
  10. 10 ​ - Setting the learning rate
  11. 11 ​ - Batched gradient descent
  12. 12 ​ - Regularization: dropout and early stopping
  13. 13 - Summary

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