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Contents

• Introduction
• 1. Dropout: A Method for Increasing Neural Network Convergence
• 2. Implementation
  
  • 2.1. Creating a New Class for Our Model
  • 2.2. Feed-Forward
  • 2.3. Feed-Backward
  • 2.4. Class Saving and Loading Methods
  • 2.5. Changes in the Neural Network Base Classes
  
  
• 3. Test
• Conclusion
• References
• Programs Used in the Article

Since the beginning of this series of articles, we have already made a big progress in studying various neural network models. But the learning process was always performed without our participation. At the same time, there is always a desire to somehow help the neural network to improve training results, which can also be referred to as the convergence of the neural network. In this article we will consider one of such methods entitled Dropout.

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