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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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• Google Research embarks on effort to map a mouse brain
  26 de September de 2023
  Posted by Michał Januszewski, Research Scientist, Google Research The human […]
• Distilling step-by-step: Outperforming larger language models with less training data and smaller model sizes
  21 de September de 2023
  Posted by Cheng-Yu Hsieh, Student Researcher, and Chen-Yu Lee, Research […]
• MediaPipe FaceStylizer: On-device real-time few-shot face stylization
  15 de September de 2023
  Posted by Haolin Jia, Software Engineer, and Qifei Wang, Senior […]

• How Will SMEs be Affected by the European Commission’s Proposal to Regulate Standard Essential Patents (SEPs)?
  27 de September de 2023
  On 27 April, the European Commission’s (EC) proposal to regulate Standard Essential Patents (SEPs) was officially made public The initiative […] The post How Will SMEs be Affected by the European Commission’s Proposal to Regulate […]

• Evaluating Cognitive Maps and Planning in Large Language Models with CogEval. (arXiv:2309.15129v1 [cs.AI])
  Recently an influx of studies claim emergent cognitive abilities in large language models (LLMs). Yet, most rely on anecdotes, overlook […]
• Active Classification of Moving Targets with Learned Control Policies. (arXiv:2212.03068v3 [cs.RO] UPDATED)
  In this paper, we consider the problem where a drone has to collect semantic information to classify multiple moving targets. […]
• TraffNet: Learning Causality of Traffic Generation for Road Network Digital Twins. (arXiv:2303.15954v4 [cs.LG] UPDATED)
  Road network digital twins (RNDTs) play a critical role in the development of next-generation intelligent transportation systems, enabling more precise […]