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EvalML: a library for automated machine learning and model understanding

EvalML is an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions, it is a library for automated machine learning (AutoML) and model understanding, written in Python

16 de May de 20212 de April de 2021

Machine Learning From Scratch

An extensive list of fundamental machine learning models and algorithms from scratch in vanilla Python.

30 de May de 2020

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• Generative AI to quantify uncertainty in weather forecasting
  29 de March de 2024
  Posted by Lizao (Larry) Li, Software Engineer, and Rob Carver, […]
• AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks
  28 de March de 2024
  Posted by Urs Köster, Software Engineer, Google Research Time series […]
• Computer-aided diagnosis for lung cancer screening
  20 de March de 2024
  Posted by Atilla Kiraly, Software Engineer, and Rory Pilgrim, Product […]

• The legacy of StandICT.eu 2026: Driving European leadership in ICT standardisation
  6 de March de 2026
  The post The legacy of StandICT.eu 2026: Driving European leadership in ICT standardisation appeared first on European DIGITAL SME Alliance.

• L2GTX: From Local to Global Time Series Explanations
  16 de March de 2026
  arXiv:2603.13065v1 Announce Type: cross Abstract: Deep learning models achieve high accuracy in time series classification, yet understanding their class-level decision […]
• MalURLBench: A Benchmark Evaluating Agents' Vulnerabilities When Processing Web URLs
  16 de March de 2026
  arXiv:2601.18113v3 Announce Type: replace-cross Abstract: LLM-based web agents have become increasingly popular for their utility in daily life and work. […]
• IROSA: Interactive Robot Skill Adaptation using Natural Language
  16 de March de 2026
  arXiv:2603.03897v2 Announce Type: replace-cross Abstract: Foundation models have demonstrated impressive capabilities across diverse domains, while imitation learning provides principled methods […]