Chapter 5. Running Your Model

In order to have a blockchain tethered AI, you first need an AI to tether. This book’s code repository includes a Traffic Signs Detection model that you can run, test, and change.

In this exercise, you will set up the Oracle Cloud that will be used to integrate your model with blockchain (Chapter 6) and the BTA (Chapter 7). You will also prepare your local environment for running Python, PyTorch, and Jupyter Notebook.

Finally, you will clone the repository that contains the sample model, gain an understanding of what files are used, and use a Jupyter Notebook to bring the model to life.

Exercise: Oracle Cloud Setup

Setting up Oracle Cloud Infrastructure (OCI) is the first step to building the BTA. This is because the cloud resources are used to securely manage and share the files shared by an AI engineering team and its stakeholders. When you set up OCI, you will create a bucket used to store objects, and then assign access to that bucket by creating groups that correspond with the staffings you will create in your BTA application. Remember as you proceed through the examples that you need to create OCI resources for each of your BTA team staffings: ai-engineer-staffing, mlops-engineer-staffing, and stakeholder-staffing.


Keep a notepad file with the information that is noted as being needed later, such as the bucket connection URLs, so you don’t have to search through OCI for it again. Be sure to use a plain-text notepad so your certificates ...

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