Machine Learning Monitoring Process: Detecting Prior Drift
Prior drift is a phenomenon that occurs when the distribution of data changes over time, causing the assumptions made about the data in...
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Kevin Slote
Applied Mathematics Researcher and Data Scientist
Kevin Slote is an academic with a of experience in Applied and Pure Mathematics. He is finishing a PhD in Mathematics and published extensively in top-tier journals. His research interests include Large Language Models, Generative AI, Dynamical Systems, and Computational Algebraic Topology. With a proven track record of excellence, Kevin is a valuable asset to any academic institution or available to consult on Generative AI, Large Language Models, and Multimodal models.
I am currently looking for post-doctoral positions.
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SERVICES
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EXPERIENCE & EDUCATION
Kevin has a strong background in data science and has worked in the NLP space for over thirteen years (before it was cool), with an educational background in both applied and pure mathematics.
Publications
Kevin's work also includes computational algebraic topology and dynamical systems.
Publications include the field of infodemiology.
[1] Kevin Daley, Kevin Slote, Rayan Succar, Roni Barak Ventura, Maurizio Porfiri, and igor Belykh. "The Twitter effect: How anti-regulation organizations drive firearm acquisitions in the United States." Manuscript submitted; 2023. DOI: 10.5281/zenodo.10631566
Patents
Through his research and projects, Kevin has demonstrated a unique blend of creativity and technical expertise.
Preprints
How do you measure false positive rates of models in production? Many data scientists have been asked this question. The sciences and literature on this question is almost non-existent. Through industry funded research we
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