Explainable AI Explained for Developers
You need to be signed in to add a collection
Nowadays, developers can easily create machine learning models with AutoML. But when you make models, you also get associated responsibilities. For example, a machine learning model is only complete if you explain the outcome. But how do you do that? And to whom do you explain? And why should you be able to do this as a Developer? In this session, you will learn why Explainable AI is an essential skill for a Developer to master when training machine learning models. In the first part of the session, you will learn why Explainable AI is important from a business perspective and why you need to know this as a Developer. In the second part of this session, you’ll learn how to explain machine learning models in practice. We’ll dive in-depth into tooling to explain machine learning models and show you how to interpret these explanations.
Transcript
Nowadays, developers can easily create machine learning models with AutoML. But when you make models, you also get associated responsibilities. For example, a machine learning model is only complete if you explain the outcome. But how do you do that? And to whom do you explain? And why should you be able to do this as a Developer? In this session, you will learn why Explainable AI is an essential skill for a Developer to master when training machine learning models.
In the first part of the session, you will learn why Explainable AI is important from a business perspective and why you need to know this as a Developer.
In the second part of this session, you’ll learn how to explain machine learning models in practice. We’ll dive in-depth into tooling to explain machine learning models and show you how to interpret these explanations.
About the speakers
Microsoft MVP & Chief AI Architect at Aigency
CTO at Aigency