The MLP Architecture: Activations & Initialization in R | CodeSignal Learn

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The MLP Architecture: Activations & Initialization in R

This course builds upon single layers to construct a complete Multi-Layer Perceptron (MLP). You'll learn to stack layers, explore different activation functions like ReLU and Softmax, and understand the importance of weight initialization for effective training.

R

4 lessons

17 practices

Less than 3 hours

Course details

The MLP Architecture: Activations & Initialization

Implementing Forward Propagation in a Multi-Layer Perceptron

Fixing Layer Dimensions in a Multi-Layer Perceptron

Building a Multi-Layer Perceptron Function in R

Expanding an MLP with an Additional Layer

Building a Multi-Layer Perceptron from Scratch in R

Previous Course Next Course: Training Neural Networks: the Backpropagation Algorithm

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