4. Červen 2023
Explainable AI, or XAI, is a rapidly expanding field of research that aims to supply methods for understanding model predictions. We will start by providing a general introduction to the field of explainability, introduce the Alibi library and focus on how it helps you to understand trained models. We will then explore the collection of algorithms provided and the types of insight they each provide, looking at a broad range of datasets and models, and discussing the pros and cons of each. In particular, we'll look at methods that apply to any model. The aim is to give the ML practitioner a clear idea of how explainability techniques can be used to justify, explore and enhance their use of ML, especially for models in deployment.
Machines can learn. Incredibly fast. Faster than you. They are getting smarter and smarter every day. They are already changing your world, your business and your life. Artificial intelligence revolution is here. Come and learn how to turn this threat into your biggest opportunity. This is not another academic conference. Our goal is to foster discussion between machine learning practitioners and all people who are interested in applications of modern trends in artificial intelligence. You can look forward to inspiring people, algorithms, data, applications, workshops and a lot of fun during three days as well as at two great parties.
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