From the course: Deep Learning: Getting Started
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Input preprocessing
From the course: Deep Learning: Getting Started
Input preprocessing
Let's now implement a deep learning model for the Iris problem described in the previous article. Code for this chapter is available in the folder chapter 04. Let's open this folder. On the left pane, we see the notebook code 04xx iris deep learning example. Clicking on it will open the notebook. You can run any code in this notebook by clicking on the Run button that is available on the left side of the cell. The first time you run it, it will prompt you to select a Python environment on the top. Clicking on Python environments will show you all the Python environments available. Make sure to select Python 3.12.1 for running examples in this course. Let's now focus on preparing input data for deep learning. Before we can train any deep learning model, we must prepare our data properly. This section goes through 5 essential steps. Loading data, converting to NumPy arrays, scaling features, encoding targets, and splitting into train and test datasets. Begin by importing our required…
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