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  • Announcing the Future of AI Engineering: Self-Optimizing Agents

    Sarah Ostermeier

    December 10, 2025
    LLMOps

    When ChatGPT launched in 2022, generative AI seemed like magic. With a simple API call and prompt, any application could…

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    Announcing the Future of AI Engineering: Self-Optimizing Agents
  • 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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  • Gideon Mendels

    April 15, 2019
    Tutorials

    Approach pre-trained deep learning models with caution

      Pre-trained models are easy to use, but are you glossing over details that could impact your model performance? How…

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    Approach pre-trained deep learning models with caution
  • Gideon Mendels

    February 15, 2019
    Industry

    Seven Myths in Machine Learning Research

      Note: this article originally appeared on Oscar Chang’s website at https://crazyoscarchang.github.io/2019/02/16/seven-myths-in-machine-learning-research/ and was reposted here with his permission. We highly encourage…

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  • Gideon Mendels

    January 16, 2019
    Machine Learning, Tutorials

    A CNN can learn Miró’ surrealism: Joan Miró Neural Style Transfer & DeepDream

      Note: this article originally appeared on Raúl Gómez’s website at https://gombru.github.io/2019/01/14/miro_styletransfer_deepdream/ and was reposted here with his permission. We highly encourage…

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    A CNN can learn Miró’ surrealism: Joan Miró Neural Style Transfer & DeepDream
  • Gideon Mendels

    November 14, 2018
    Tutorials

    Real-time numbers recognition (MNIST) on an iPhone with CoreML from A to Z

    Learn how to build and train a deep learning network to recognize numbers (MNIST), how to convert it in the…

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  • Gideon Mendels

    August 6, 2018
    Tutorials

    Building reliable machine learning models with cross-validation

    Cross-validation is a technique used to measure and evaluate machine learning models performance. During training we create a number of…

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    Building reliable machine learning models with cross-validation
  • Gideon Mendels

    July 10, 2018
    Machine Learning

    A Data Scientist’s Guide to Communicating Results

    So your model is finally done running, you’ve tweaked and optimized all of the hyperparameters you could to obtain the…

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    A Data Scientist’s Guide to Communicating Results
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