AI webinar: Explainability and Bias in AI
Details
This is online live tech talk. You will join online using zoom.us (video conference tool), and watch, follow, Q&A with speakers from anywhere around the world. Miss the live session due to time zone or conflict? you can learn session replay at any time afterwards.
AI webinar: Explainability and Bias in AI
Start date/time: Aug 9th, 10am-11am PT (US pacific time), check your local time.
Registration:
https://learn.xnextcon.com/event/eventdetails/W19080910
(you must register at the website to receive the link to join the workshop online).
Details:
There is a growing need both for machine learning models that are explainable and models that are fair and free from bias. In this two-part talk, we will present an introduction to explainability and bias in machine learning.
In the first part, we will start with an overview of techniques, such as LIME and SHAP, for explaining machine learning models. In addition to helping us explain models and their predictions, explainability methods can also help us debug and find flaws in our models. In the second part of the talk, we will then go over some of the state-of-the-art methods for detecting and mitigating bias, and talk briefly about general challenges in handling bias.
Make sure to register at: https://learn.xnextcon.com/event/eventdetails/W19080910
after you sign up and enroll to this webinar, you will receive an unique link to join online.