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  • Quick Start
  • Introduction

Models & Functions

  • Neural Network - Model
  • Architecture Layers - Model
  • Data - Model
  • Activation - Functions
  • Loss - Functions

Layers

  • Embedding layer (Input)
  • Fully Connected (Dense)
  • Recurrent Neural Network (RNN)
  • Long Short-Term Memory (LSTM)
  • Gated Recurrent Unit (GRU)
  • Convolution 2D (CNN)
  • Pooling (CNN)
  • Dropout - Regularization
  • Flatten - Adapter

Examples and more

  • Data preparation - Examples
  • Network training - Examples
  • Expert Documentation
  • Appendix
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