Deep Neural Networks
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01. Non-linear Data
02. Continuous Perceptrons
03. Non-Linear Models
04. Neural Network Architecture
05. Feedforward
06. Backpropagation
07. Keras
08. Pre-Lab: Student Admissions in Keras
09. Lab: Student Admissions in Keras
10. Training Optimization
11. Early Stopping
12. Regularization
13. Regularization 2
14. Dropout
15. Local Minima
16. Vanishing Gradient
17. Other Activation Functions
18. Batch vs Stochastic Gradient Descent
19. Learning Rate Decay
20. Random Restart
21. Momentum
22. Optimizers in Keras
23. Error Functions Around the World
24. Neural Network Regression
25. Neural Networks Playground
26. Mini Project Intro
27. Pre-Lab: IMDB Data in Keras
28. Lab: IMDB Data in Keras
29. Outro
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19. Learning Rate Decay
Learning Rate
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