How to Use Python to Build an Artificial Neural Network for Classification
In this episode, we're going to build a simple A.I. model in Python that will classify our customers as to whether they will join our "preferred" customer program or not. We'll get our training and testing data, build a model, fit it, predict results, and then test those results for accuracy against real world numbers. By letting a computer learn from our data, we can derive useful information that could help set us up for success. By using this data, we can make better decisions, saving time and resources. My goal with this model is to demonstrate one of the simplest implementations of an artificial neural network (ANN) from start to finish, in a Supervised model, using Tensorflow and the Keras libraries. You can apply this model to your own data to see if there are opportunities to use AI's classification techniques.
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How to Use Python to Build an Artificial Neural Network for Classification
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