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Agile Artificial Intelligence in Pharo: Implementing Neural Networks, Genetic Algorithms, and Neuroevolution
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Agile Artificial Intelligence in Pharo: Implementing Neural Networks, Genetic Algorithms, and Neuroevolution

by Alexandre Bergel
June 2020
Beginner to intermediate
394 pages
7h 17m
English
Apress
Content preview from Agile Artificial Intelligence in Pharo: Implementing Neural Networks, Genetic Algorithms, and Neuroevolution
© Alexandre Bergel​ 2020
A. BergelAgile Artificial Intelligence in Pharohttps://doi.org/10.1007/978-1-4842-5384-7_6

6. A Matrix Library

Alexandre Bergel1 
(1)
Santiago, Chile
 

In the previous chapters, we presented an implementation of a neural network made of layers and neurons (i.e., instances of NeuronLayer and Neuron). Although instructive, that implementation does not reflect classical ways of implementing a neural network. A layer can be expressed as a matrix of weights and a vector of biases. This is how most libraries that build neural networks (e.g., TensorFlow and PyTorch) actually operate.

This chapter lays out a small library to build and manipulate matrices. This chapter is an important foundation for the subsequent chapter, which is about ...

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