Benefits of using a neural network for regression

For the rest of this chapter, we will focus on using deep neural networks to make a prediction. When compared to using traditional multiple linear regression, you'll be pleased to find that our neural network has the following advantages:

  • We don't need to select or screen features. Neural networks are amazing feature engineering machines and can learn what features are relevant and ignore the irrelevant ones.
  • Given an adequately complex network, feature interactions are also learned (for example, the effect of x1 * x2 in addition to the independent effects of x1 and x2)
  • As you have maybe guessed by now, we can also learn higher order polynomial relationships (for example, x23 )
  • And lastly, ...

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