Multi-Layer-Perceptron-for-Multi-Class-Classification

A multi-layer perceptron is a group of connected logistic regression units (MLP). During training, MLP employs the supervised learning technique known as backpropagation. This study will discuss the creation of the complete method for training an MLP for multi-class classification. The development of the multi-layer perceptron method will also be presented. The backpropagation algorithm will be covered in order to comprehend how a neural network can be taught. The whole theory presented in these sections will be converted into Python code as part of this paper's main goal. The theory-based development of a multi-layer perceptron in code is demonstrated in this study. The application of concepts like adaptive learning rates, momentum, mini-batch gradient descent, and bias correction improves training effectiveness.

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