How Machines Decide: From Artificial Neurons to Deep Learning

Have you ever wondered how self-driving cars know when to stop or turn? Or how streaming platforms seem to know exactly what you want to watch next? Join ASU Library's Unit for Data Science and Analytics for the second session of our foundational mini-series as we continue exploring the mathematics and decision-making processes behind modern AI systems.

In this session, we will build on the ideas introduced in the Open Lab titled “Understanding Classification with Logistic Regression” to understand how neural networks and deep learning patterns enable machines to learn patterns and make decisions. We will discuss how probabilities and mathematical functions work together inside artificial neurons, how groups of neurons form networks capable of recognizing patterns, and what it really means when people say a model is “deep.” But what exactly is an artificial neuron, and how can thousands or even millions of them work together to make decisions? Join us to explore the foundations of deep learning and learn how these systems are trained to identify patterns in data using open-source (free) tools.

As a foundational series, this session is designed for a beginner-to-intermediate audience. Along the way, we will connect these ideas to everyday technologies like self-driving cars, recommendation systems, image recognition, voice assistants, and generative AI tools. No matter where you are in your data journey, come join us to learn, explore, and strengthen your understanding of how modern AI systems learn from data!