Building Our Adversarial Playground
In Chapter 1, we introduced core concepts of artificial intelligence (AI) and machine learning (ML) to help lay the foundations for working with adversarial AI. In this chapter, we will provide a hands-on walkthrough of ML development, demonstrating how to create and manage your development environment, utilize the algorithms, and navigate the life cycle we described. We will build models and deploy a neural network (NN) model as a REST prediction service. This will be our adversarial playground, the target of our adversarial AI attacks.
By the end of the chapter, you will have learned how to do the following:
- Install Python and create a Python virtual environment to manage your dependencies and work.
- Install Python packages required for data analysis and ML.
- Register our virtual environment as a Jupyter Notebook kernel.
- Use a Jupyter notebook to explore baseline ML algorithms and a simple Keras NN for classifying wine samples...
