Building an Artificial Neural Network with TensorFlow 2

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Building an Artificial Neural Network with TensorFlow 2

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In this guide, we will learn how to build an Artificial Neural Network (ANN) with TensorFlow 2. One application of machine learning in business is predicting customers that will churn. If we know the customers that will churn, we can provide special services to them. We do not want to lose any customers. We will build and train an Artificial Neural Network to predict customers that will churn from a bank using the customer-churning dataset from Kaggle. Some features of the dataset we will use are credit score, country, gender, age, tenure, balance, etc. After reading this guide, you will be able to build an ANN to solve binary classification problems with any dataset.

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Label Encoding & One-Hot Encoding Categorical Variables,
Build and visualize model architecture with Keras visualizer,
Compile and train an ANN with Keras on top of TensorFlow 2,
Make Predictions on a new customer,
Check the model's accuracy score and create a confusion matrix.

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https://keras.io/api/

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