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  • From Observability to Optimization: Announcing the Opik Agent Optimizer Public Beta

    Vincent Koc

    May 21, 2025
    LLMOps, Product

    At Comet, we’re driven by a commitment to advance innovation in AI, particularly in the realm of LLM observability. Our…

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    From Observability to Optimization: Announcing the Opik Agent Optimizer Public Beta
  • Dhruv Nair

    April 20, 2020
    Comet Community Hub, Product

    Predictive Early Stopping – A Meta Learning Approach

    Introduction Model training is arguably the most time consuming, and computationally demanding part of the Machine Learning pipeline. Depending on…

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    Predictive Early Stopping – A Meta Learning Approach
  • Nikolas Laskaris

    March 25, 2020
    Partners & Integrations

    New Integration: Comet + PyTorch Lightning

    Machine learning practitioners can now use PyTorch Lightning with Comet to speed up research cycles and build better models, faster.…

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    New Integration: Comet + PyTorch Lightning
  • Nikolas Laskaris

    March 20, 2020
    Industry

    How to Make Remote Work Effective for Data Science Teams

    This article was written in collaboration with Tyler Folkman, Head of AI at Branded Entertainment Network. To read more of…

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    How to Make Remote Work Effective for Data Science Teams
  • Nikolas Laskaris

    December 4, 2019
    Machine Learning

    Why software engineering processes and tools don’t work for machine learning

    While AI may be the new electricity significant challenges remain to realize AI potential. Here we examine why data scientists…

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    Why software engineering processes and tools don’t work for machine learning
  • Nikolas Laskaris

    November 18, 2019
    Machine Learning, Tutorials

    How to apply machine learning and deep learning methods to audio analysis

    To view the code, training visualizations, and more information about the python example at the end of this post, visit…

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    How to apply machine learning and deep learning methods to audio analysis
  • Gideon Mendels

    October 24, 2019
    Machine Learning

    Stanford Research Series: Grand Digital Piano: Multimodal Transfer of Learning of Sound and Touch

    Authors: Ernesto Evgeniy Sanches Shayda (esanches@stanford.edu), Ilkyu Lee (lqlee@stanford.edu) I. MOTIVATION Musical instruments have evolved during thousands of years allowing…

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    Stanford Research Series: Grand Digital Piano: Multimodal Transfer of Learning of Sound and Touch
  • Dhruv Nair

    October 18, 2019
    Comet Community Hub, Machine Learning

    Estimating Uncertainty in Machine Learning Models — Part 3

      Check out part 1 (here)and part 2 (here) of this series In the last part of our series on…

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    Estimating Uncertainty in Machine Learning Models — Part 3
  • Gideon Mendels

    October 2, 2019
    Machine Learning

    Stanford Research Series: Making Trading Great Again: Trump-based Stock Predictions via doc2vec Embeddings

    Authors: Rifath Rashid (rifath@stanford.edu) and Anton de Leon (aadeleon@atanford.edu) 1 Introduction The question of how accurately Twitter posts can model…

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    Stanford Research Series: Making Trading Great Again: Trump-based Stock Predictions via doc2vec Embeddings
  • Dhruv Nair

    September 26, 2019
    Comet Community Hub, Machine Learning

    Estimating Uncertainty in Machine Learning Models – Part 2

      You can check out part 1 of this series here In part 1 of this series, we discussed the sources…

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    Estimating Uncertainty in Machine Learning Models – Part 2
  • Gideon Mendels

    September 25, 2019
    Partners & Integrations

    Stanford Research Series: Climate Classification Using Landscape Images

    Authors: Drake Johnson (drakej@stanford.edu), Tim Ngo (ngotm@stanford.edu), Augusto Fernandez (afyrxr@stanford.edu) I. Introduction: Recently, there has been an increase in interest…

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    Stanford Research Series: Climate Classification Using Landscape Images
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