Data and AI are essential across all business areas. There is a broad and growing spectrum: from Machine Learning to Neural Networks, from Chatbots to AI in IT Operations…
This session is all about Trusted AI
We are just in the middle of the Deep Learning hype. Enterprises are still struggling with production deployments. What’s holding them back? One of the reasons is that untrusted AI raises a lot of concerns. In this talk we’ll explain data lineage, bias detection, adversarial robustness and model explainability, and how this can be achieved using open source.
During this hour Romeo Kienzler will show us how to build reproducible, unbiased, and robust AI Pipelines using the python Open Source stack.
- Introduction to the key concerns on large scale AI adoption in the Enterprise
- Explanation of the terms data lineage, bias detection, adversarial robustness and model explainability
- Presentation of an open source framework to mitigate these aspects
Romeo Kienzler is CTO and Chief Data Scientist at IBM in Switzerland. As a Coursera Instructor and Senior Technical Staff Member he has deep knowledge in the area of Data Science, Machine Learning and Deep Learning… Come and see for yourself.
☁️ Free IBM Cloud Account: https://ibm.biz/BdfcAj
This webinar will be livestreamed on Crowdcast.
➡ Please register in advance, if you can: https://www.crowdcast.io/e/data-ai-series-ai-pipelines
Instructions on how to setup your device for Crowdcast can be found here: https://www.crowdcast.io/setup
Data & AI Demystified – Your Path to AI.
Join us in this series – every Tuesday – discover more about these technologies. Learn how to infuse your applications and processes with AI, and ultimately accelerate your innovation and growth. Let’s climb the AI ladder together.
In case you missed any of the previous sessions in our series and are interested to learn more, you can find the replays here: https://ibm.biz/aiseries2021