Differential Machine Learning by Brian Huge & Antoine Savine
differential-machine-learning
Demonstration notebooks and additional material for the Risk articles on differential machine learning by Brian Huge and Antoine Savine (2020-2021)
Danske Bank Copenhagen
Tianzi Cai
anguillanneuf
2003-04: C++ | 14: R | 15: Python | 16: Spark, TensorFlow | 17: Self-driving car | 18: big O, Pub/Sub | 19: Go, RL | 20: Spring
@GoogleCloudPlatform Mountain View, CA
Yves Hilpisch
yhilpisch
CEO The Python Quants & The AI Machine | Python, AI, GenAI for Quant Finance, Asset Management, and Algorithmic Trading
The Python Quants | The AI Machine Germany
Tim Sweña (Swast)
tswast
Software Engineer @GoogleCloudPlatform. I also hack on personal projects, mostly related to math & pixels.
Google Chicago, IL
Nikhil Kothari
nikhilk
Engineering Lead @google, working on machine learning and data analytics services for Google Cloud Platform.
Google Seattle
Chris Mattmann
chrismattmann
Chief Data and AI Officer, @ucla
Adjunct Research Prof @USCDataScience
ex @nasa-jpl
ex Board of Directors @apache
Mattmann.AI La Canada Flintridge, CA
FemtoTrader
femtotrader
Geek (or nerd?), physics/electrical engineering teacher in higher education and amateur trader (trying to become a much more advised investor ;-)
France
Josh Wills
jwills
Member of Technical Staff @ DatologyAI, creator of dbt-duckdb
N/A San Francisco, CA
Sean Owen
srowen
Applied research @ Mosaic @ Databricks. Formerly Principal DS/ML Specialist @ Databricks. Apache Spark PMC / committer. Primary author, zxing and Oryx project.
@databricks Austin, TX