William Overman
  • Bio
  • Papers
  • Recent & Upcoming Talks
    • Example Talk
  • Publications
    • Can We Validate Counterfactual Estimations in the Presence of General Network Interference?
    • Aligning Model Properties via Conformal Risk Control
    • Higher-Order Causal Message Passing for Experimentation with Complex Interference
    • Improved Regret Bound for Safe Reinforcement Learning via Tighter Cost Pessimism and Reward Optimism
    • Occupancy Prediction with Patient Data: Evaluating Time-Series, Patient-Level Aggregation, and Deep Set Models
    • Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
    • Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games
    • Independent Natural Policy Gradient always converges in Markov Potential Games
    • Some Ordered Ramsey Numbers of Graphs on Four Vertices
  • Projects
  • Blog
    • 🎉 Easily create your own simple yet highly customizable blog
    • 🧠 Sharpen your thinking with a second brain
    • 📈 Communicate your results effectively with the best data visualizations
    • 👩🏼‍🏫 Teach academic courses
    • ✅ Manage your projects
  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
  • Experience
  • Teaching
    • Learn JavaScript
    • Learn Python

scikit-learn

Oct 26, 2023 · 1 min read
Go to Project Site

scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.

Last updated on Oct 26, 2023
Hugo Wowchemy Markdown
William Overman
Authors
William Overman
PhD Student
← PyTorch Oct 26, 2023

© 2025 Me. This work is licensed under CC BY NC ND 4.0

Published with Hugo Blox Builder — the free, open source website builder that empowers creators.