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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a TRAFFIC COUNTING (TC) PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
You will be writing classes that represent various parts of a vending machine. You will need to write two files: VendingMachine.java and VendingItem.java. A simple driver class VendingWorld.java has been provided, and it will allow you to interact with your simulation. Specific instructions for each file are given in later sections.
✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a HEARING PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an OBJECT MASKING PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION (C) proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).