IBM Open Source AI + TensorFlow Extended (TFX) + KubeFlow + Kubernetes + Airflow

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When:  Jun 27, 2019 from 06:00 PM to 09:00 PM (PT)
Thanks to IBM Data Science Community for hosting the event at 425 Market street SF, and offering to provide the refreshments.

Join the IBM Data Science Community https://www.ibm.com/community/datascience/ and participate in shaping the digital future.

Doors Open: 6:00pm
Talks Start: 6:30pm
Mingle: 8:30pm
End: 9:00pm

Agenda

1. Intro IBM (5 mins)

2. Meetup Updates and Announcements (5 mins)

3. IBM Open Source AI: How to prepare your AI for the next wave of regulations: Trust and Transparency in ML life cycles (30 mins)
Speaker: Sepideh Seifzadeh, PhD (https://www.linkedin.com/in/sepiseif/)

In this talk, we demonstrate how to operationalize machine learning algorithms and monitor and manage the deployed models. We also cover how to evaluate the models that have been operationalized in production to track and measure the impact of AI on business outcomes, drive fair outcomes and explain decisions to comply with regulations and govern AI to adapt AI to changing business situation. We also talk about model explainability feature which helps us to better understand why a certain algorithm has come up with certain decisions, and how to detect and mitigate the bias to have fair decisions.

4. KubeFlow + Keras/TensorFlow 2.0 + TF Extended (TFX) + Kubernetes + Airflow + Jupyter (30 mins)
Speaker: Chris Fregly, Founder @ PipelineAI (https://linkedin.com/in/cfregly)

In this talk, we demonstrate a real-world machine learning pipelines using TensorFlow Extended (TFX), KubeFlow, and Airflow.

Described in the 2017 paper, TFX is used internally by thousands of Google data scientists and engineers across every major product line within Google.

KubeFlow is a modern, end-to-end pipeline orchestration framework that embraces the latest AI best practices including hyper-parameter tuning, distributed model training, and model tracking.

Airflow is the most-widely used pipeline orchestration framework in machine learning.
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Contact

SEPIDEH Seifzadeh
6282300677
sepi@ibm.com