Deep Learning with Redshift ML
We explored supervised learning in Chapters 6 and 7 and unsupervised learning models in Chapter 8. In this chapter, we will explore deep learning algorithms, a multilayer perceptron (MLP), which is a feedforward artificial neural network (ANN), and understand how it handles data that is not linearly separable (which means the data points in your data cannot be separated by a clear line). This chapter will provide detailed steps on how to perform deep learning in Amazon Redshift ML using MLP. By the end of this chapter, you will be in a position to identify a business problem that can be solved using MLP and know how to create the model, evaluate the performance of the model, and run predictions.
In this chapter, we will go through the following main topics:
- Introduction to deep learning
- Business problem
- Uploading and analyzing the data
- Creating a multiclass classification model using MLP
- Running predictions
