Layers

This part of the documentation helps to understand how to combine layers into networks. It covers basics and some of the more advanced topics.

These topics are relevant only to the deep learning models.

• Basics
  • Join layers
  • Inline operator
  • Input layer
  • Build networks from the code
• Mutlilayer Perceptron (MLP)
• Convolutional Neural Networks (CNN)
  • Reshape
  • Convolution
  • Pooling
• Parallel connections
• Create custom layers
  • Element-wise transformation
  • Layers with activation function
  • Layer that modifies input shape
  • Layer that accepts multiple inputs
  • Add parameters to the layer
• Parameter Initialization Methods
  • Create custom initialization methods
  • Share parameters between layers
• Debug layer connections
  • Input and output shapes
  • Visualize networks
  • Count number of parameters
  • Iterate through all network parameters

• « Documentation
• Basics »

Search

Install NeuPy

pip install neupy

Learn more about NeuPy reading tutorials and documentation.

Issues and feature requests

If you find a bug or want to suggest a new feature feel free to create an issue on Github