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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
  • Gideon Mendels

    September 19, 2019
    Machine Learning

    Stanford Research Series: Exploring Model Architectures and View-Specific Models for Chest Radiograph Diagnoses

    Authors: Danny Takeuchi (dtakeuch@stanford.edu), Raymond Thai (raythai@stanford.edu), Kevin Tran (ktran23@stanford.edu) This project tackles several current issues with automated chest X-ray…

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    Stanford Research Series: Exploring Model Architectures and View-Specific Models for Chest Radiograph Diagnoses
  • Dhruv Nair

    September 12, 2019
    Comet Community Hub, Machine Learning

    Estimating Uncertainty in Machine Learning Models — Part 1

      “We demand rigidly defined areas of doubt and uncertainty!” – Douglas Adams, The Hitchhiker’s Guide to the Galaxy Why…

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    Estimating Uncertainty in Machine Learning Models — Part 1
  • Nikolas Laskaris

    September 4, 2019
    Comet Community Hub, Product, Tutorials

    Getting Started with Natural Language Processing: US Airline Sentiment Analysis

    Sections Introduction to NLP Dataset Exploration NLP Processing Training Hyperparameter Optimization Resources for Future Learning Introduction to NLP Natural Language…

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    Getting Started with Natural Language Processing: US Airline Sentiment Analysis
  • Gideon Mendels

    August 20, 2019
    Machine Learning

    Selecting the right weight initialization for your deep neural network

      Part 1 of a two part series The weight initialization technique you choose for your neural network can determine…

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    Selecting the right weight initialization for your deep neural network
  • Gideon Mendels

    August 13, 2019
    Academic Research

    Research Series: Understanding Generalization through Visualizations

    By Ronny Huang, July 2019   Ronny Huang is a postdoc student at The University of Maryland and researcher in residence…

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    Research Series: Understanding Generalization through Visualizations
  • Gideon Mendels

    August 6, 2019
    Comet Community Hub, Partners & Integrations, Product

    Building reliable machine learning pipelines with AWS Sagemaker and Comet

    This tutorial is Part II of a series. See Part I here. Successfully executing machine learning at scale involves building reliable…

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    Building reliable machine learning pipelines with AWS Sagemaker and Comet
  • Gideon Mendels

    July 24, 2019
    Comet Community Hub, Product, Tutorials

    Codeless Deep Learning Pipelines with Ludwig and comet.ml

    How to use Ludwig and comet.ml together to build powerful deep learning models right in your command line — using…

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    Codeless Deep Learning Pipelines with Ludwig and comet.ml
  • Gideon Mendels

    July 17, 2019
    Comet Community Hub, Product

    Building a DevOps Pipeline for Machine Learning and AI: Evaluating Sagemaker

    The rush to build and deploy machine learning models has exposed cracks in traditional DevOps processes.   Infrastructure built for…

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    Building a DevOps Pipeline for Machine Learning and AI: Evaluating Sagemaker
  • Gideon Mendels

    May 24, 2019
    Comet Community Hub, Machine Learning, Product

    Organizing Machine Learning Projects: Project Management Guidelines

      Author: Jeremy Jordan Originally published at https://www.jeremyjordan.me on September 1, 2018, and was updated recently to reflect new resources. The goal…

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    Organizing Machine Learning Projects: Project Management Guidelines
  • Gideon Mendels

    May 13, 2019
    Machine Learning

    Building a fully reproducible machine learning pipeline with comet.ml and Quilt

    Classifying fruits using a Keras multi-class image classification model and Google Open Images   This post was written in collaboration…

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