Scala: Guide for Data Science Professionals

Summary

This concludes not only the journey inside the multilayer perceptron, but also the introduction of the supervised learning algorithms. In this chapter, you learned:

• The components and architecture of a neural networks
• The stages of the training cycle of a backpropagation multilayer perceptron
• How to implement an MLP from the ground up in Scala
• The numerous configuration parameters and options to use MLP as a classifier and regression
• To evaluate the impact of the learning rate and the gradient descent momentum factor on the convergence of the sum of squared errors during training
• How to apply a multilayer perceptron to the financial analysis of the fluctuation of currencies

The next chapter will introduce the concept of genetic algorithms with ...