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    The Importance of Machine Learning Model Validation and How It Works

    Model valuation is a core component of developing machine learning or artificial intelligence (ML/AI). While it’s separate from training and deployment, it should pervade the...

    Machine Learning Model Training: What It Is and Why It’s Important

    Training a machine learning (ML) model is a process in which a machine learning algorithm is fed with training data from which it can learn. ML...

    A Guide to Machine Learning Model Development and Production

    Machine learning is a subset of artificial intelligence (AI) that uses algorithms to learn from trends, data sets and certain behaviors. This process...

    The Role of Containers on MLOps and Model Production

    Container technology has changed the way data science gets done. The original container use case for data science focused on what I call,...

    Model Interpretability: The Conversation Continues

    This Domino Data Science Field Note covers a proposed definition of interpretability and distilled overview of the PDR framework. Insights are drawn...

    Understanding Causal Inference

    This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data...

    Themes and Conferences per Pacoid, Episode 11

    Paco Nathan's latest article covers program synthesis, AutoPandas, model-driven data queries, and more. Introduction Welcome back to our monthly...

    Product Management for AI

    Pete Skomoroch presented “Product Management for AI” at Rev. This post provides a distilled summary, video, and full transcript. Session Summary ...

    Announcing Domino 3.4: Furthering Collaboration with Activity Feed

    Our last release, Domino 3.3 saw the addition of two major capabilities: Datasets and Experiment Manager. “Datasets”, a high-performance, revisioned...

    Themes and Conferences per Pacoid, Episode 9

    Paco Nathan's latest article features several emerging threads adjacent to model interpretability. Introduction Welcome back to our monthly burst of...

    Manipulating Data with dplyr

    Special thanks to Addison-Wesley Professional for permission to excerpt the following "Manipulating data with dplyr" chapter from the book, ...

    Domino 3.3: Datasets and Experiment Manager

    Our mission at Domino is to enable organizations to put models at the heart of their business. Models are so different from software — e.g., they...