Causal Machine Learning for Industrial Root Cause Analysis: something I'd been working on. The first part of the post introduces the concepts, and the second part demonstrates its application in a manufacturing setting using DoWhy.
https://t.co/4edUkTeMM0
Something I have been working on since I joined Databricks: a large-scale forecasting solution accelerator. Finally managed to write a blog post: Introducing Many Model Forecasting (MMF) by Databricks https://t.co/ScaiKAXhpq
Something I have been working on: RLAIF. Model alignment is crucial. RLHF is an effective way to guide your model to alignment, but the label collection can be cost prohibitive. We propose an AI-based solution for the reward mechanism in this work 🤖
https://t.co/cXssgPa75m
I wrote an article on casual inference and decision making. Something that I have been working on recently.
“Causal Machine Learning” by Ryuta Yoshimatsu
https://t.co/omsOucxu56
“If magic comes from putting brilliant minds in the same room, we’re building Tribe to be that room.”
Hear from our founders @jacsrice and @wis3foo1 about what they’ve learned building @tribe_ai and why the future of ML will be project based.
https://t.co/onhP2OzoCt
Our consultants Inna and Ryuta shared their stories as Data Analytics Consultants with students from the Computational Business Analytics Bachelor’s program at Frankfurt School of Finance and Management. Main focus was real world examples of various aspects of data science.
Join us this weekend during the ACE Datathon. On Saturday during the Career Fair and in the afternoon Ryuta Yoshimatsu will lead a workshop to kickstart your coding!
Looking forward to seeing you there!
More infos here 👉https://t.co/QdeYAku4zS
#datathon#analytics#datascience
Computational Business Analytics—Practitioner Series, Fri April 16, 3:30–4:30 CET:
Dr. Ryuta Yoshimatsu (@RyutaZurich) & Inna Grijnevitch (https://t.co/HTT5rDSGZg) “Cross topics on data analytics, engineering, visual analytics…”
Link: https://t.co/awFAwBwUsD
Monthly subscription for your sneakers. You pay a fixed price and can exchange your sneakers whenever they go bad (exists already: https://t.co/eMnd4VMlUm )
Toilet rating platform. The service provides information about the location, fee, cleanness, crowdedness, etc. of public and semi-public (restaurants, shops, etc.) bathrooms that are you get form your users.