Connect With the Best Minds in Data Science and Machine Learning
We host private events that allow people to be able to discuss the most pertinent ideas in Machine Learning and deep dive with the most interesting minds in industry.
Our events are live and online and come in three flavors:
We host private events where the best minds share their insights about the world of Machine Learning, with an emphasis on industry best practices.
Dive deep into a particular subset of Machine Learning, where we look underneath the hood of the most popular tools and make changes to actual source code.
An open forum where curious enthusiasts get together to learn about the latest developments in the field. Mind candy for the intellectually curious.
Experimental Design with Text Message Data
How to conduct experiments with text at scale
Laura Zheng
Causal Inference and Machine Learning: The Current Frontier
How to Combine Counterfactuals with Pattern Recognition
Gerard Torrats-Espinosa
DSML Group. Private Dinner
Join other DSML Group Attendees for a Private Dinner
Jonathan Bechtel
Research Reading: Prototyping Conversational LLM's With Alpaca
Fast and Easy Chatbots
Jonathan Bechtel
Modeling The World With Large GeoSpatial Models
LGMs will be to location what LLMs are for Language
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Konstantin Klemmer
Using Machine Learning to Study the Structure of CryptoMarkets
What is the underlying graph structure of the crypto financial market?
Jonathan Bechtel
Using Machine Learning in E-Commerce w/ Rokt
Join us at Rokt on-site to learn how a leader in e-commerce technology uses ML to solve problems.
Yan Xu
Advanced Basketball Analytics With DARKO
Learn about advanced basketball analytics with the creator of DARKO
Konstantin Medvedovsky
Research Reading: Replacing Back-Propagation With The Forward-Forward Algorithm
Is it possible to replace back-propagation?
Jonathan Bechtel
Advances in Bayesian Inference for Model Generalization
For model generalization, the conditional > the marginal likelihood
Sanae Lotfi
Segregation and COVID Vaccination Rates: A Machine Learning Approach
Learning how you can use machine learning to better understand social behavior and public health outcomes
Jared Lewis
Data Science for Demand Forecasting and Supply Chain Optimization
The latest frontier in quantitative methods for time series and optimization problems
Nicolas Vandeput
A Primer on Missing Data Methods for Data Scientists
Best practices for thinking about and interpreting missing data when doing data science.
Heather Harris
Insights and Innovations in Natural Language Processing
The current state of the NLP ecosystem, explained to a broad audience.
Viviana Márquez
The Evolution of the Data Ecosystem
A discussion on how roles in ML and Data Science have evolved over time
TJ Bay
Using Machine Learning & NLP Advances To Enhance Search And Discovery
How new advances in deep learning have impacted the way search works in the web
Grant Ingersoll
Estimating Covid-19 Racial Disparity Using Machine Learning
Using machine learning to understand the causal effect of segregation on Covid mortality
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Gerard Torrats-Espinosa
Using ML to Catch Fraud in Live Event Ticketing
How to use ML to Detect Anomalies At Scale
Kjell Sawyer
Anatomy of an ML Codebase
Don't settle for knowing how to use an ML tool, understand how to build it.
Jonathan Bechtel
Research Reading: Fine-Tuning Stable Diffusion Models with SVD
Can you tame the biggest neural networks by training on its singular values? Join us to read a paper and find out.
Jonathan Bechtel
How to Use Causal Inference in Machine Learning
For some problems you don't just need more data, you need a counterfactual.
Gerard Torrats-Espinosa
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Behind the Black Box: How to Understand Any ML Model Using SHAP
Use SHAP to interpret the patterns found in the most powerful ML models such as neural networks and gradient boosting.
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